{"title":"AI Dev Kits","description":"","products":[{"product_id":"nvidia-jetson-agx-orin-developer-kit-64gb","title":"طقم تطوير NVIDIA Jetson AGX Orin (سعة 64 جيجابايت)","description":"\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003eتتضمن مجموعة تطوير NVIDIA® Jetson AGX Orin™ وحدة Jetson AGX Orin عالية الأداء وموفرة للطاقة، ويمكنها محاكاة وحدات Jetson Orin الأخرى. أصبح لديك الآن ما يصل إلى 275 تريليون عملية في الثانية (TOPS) وأداء يعادل 8 أضعاف أداء NVIDIA® Jetson AGX Xavier™ في نفس عامل الشكل المدمج لتطوير الروبوتات المتقدمة ومنتجات الآلات المستقلة الأخرى.\u003c\/p\u003e\n\u003cp\u003eبفضل دعم NVIDIA JetPack™ ومنصات البرمجيات الخاصة بحالات الاستخدام، بما في ذلك Isaac للروبوتات، وMetropolis للمدن الذكية، توفر مجموعة التطوير هذه كل ما تحتاجه للبدء على الفور.\u003c\/p\u003e\n\u003ch3 class=\"hdln--l\"\u003eمحتويات مجموعة التطوير\u003c\/h3\u003e\n\u003cul\u003e\n\n\u003cli\u003eوحدة Jetson AGX Orin مع مشتت حراري ولوحة حاملة مرجعية\u003c\/li\u003e\n\n\u003cli\u003eوحدة تحكم واجهة الشبكة اللاسلكية 802.11ac\/abgn\u003c\/li\u003e\n\n\u003cli\u003eمحول طاقة USB-C وسلك\u003c\/li\u003e\n\n\u003cli\u003eدليل البدء السريع والدعم\u003c\/li\u003e\n\n\u003cli\u003e\u003cspan style=\"color: #ff2a00;\"\u003eملاحظة: هناك مهلة زمنية مدتها 5 أيام بعد تقديم الطلب.\u003c\/span\u003e\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003cp class=\"content-l\" data-mce-fragment=\"1\"\u003e \u003cmeta charset=\"UTF-8\"\u003e\u003c\/p\u003e\n\u003ch3 class=\"hdln--l\"\u003eالمواصفات التقنية\u003c\/h3\u003e\n\u003cdiv class=\"row\"\u003e\n\n\u003cdiv class=\"col-md-3\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv class=\"col-md-6\"\u003e\n\n\u003ctable class=\"table table-bordered\"\u003e\n\n\u003cthead\u003e\n\n\u003ctr\u003e\n\n\u003cth colspan=\"2\"\u003eوحدة JETSON AGX ORIN\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eوحدة معالجة الرسومات (GPU)\u003c\/th\u003e\n\n\u003cth\u003eمعمارية NVIDIA Ampere مع 2048 نواة NVIDIA® CUDA® و64 نواة تينسور (Tensor)\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eوحدة المعالجة المركزية (CPU)\u003c\/th\u003e\n\n\u003cth\u003eوحدة معالجة مركزية Arm Cortex-A78AE v8.2 بـ 12 نواة 64 بت \u003cbr\u003e3 ميجابايت L2 + 6 ميجابايت L3\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eمسرع التعلم العميق (DL Accelerator)\u003c\/th\u003e\n\n\u003cth\u003e2x NVDLA v2.0\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eمسرع الرؤية\u003c\/th\u003e\n\n\u003cth\u003ePVA v2.0\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eالذاكرة\u003c\/th\u003e\n\n\u003cth\u003e64 جيجابايت 256 بت LPDDR5 \u003cbr\u003e204.8 جيجابايت\/ثانية\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eالتخزين\u003c\/th\u003e\n\n\u003cth\u003e64 جيجابايت eMMC 5.1\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eترميز الفيديو\u003c\/th\u003e\n\n\u003cth\u003e2x 4K60 | 4x 4K30 | 8x 1080p60 | 16x 1080p30 (H.265)\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eفك ترميز الفيديو\u003c\/th\u003e\n\n\u003cth\u003e1x 8K30 | 3x 4K60 | 6x 4K30 | 12x 1080p60 | 24x 1080p30 (H.265)\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/thead\u003e\n\n\u003ctbody\u003e\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\u003cp class=\"content-s\"\u003eراجع قسم ميزات البرامج في أحدث دليل لمطوري NVIDIA Jetson Linux للحصول على قائمة بالميزات المدعومة.\u003c\/p\u003e\n\n\u003cbr\u003e\n\u003ctable class=\"table table-bordered\"\u003e\n\n\u003cthead\u003e\n\n\u003ctr\u003e\n\n\u003cth colspan=\"2\"\u003eاللوحة الحاملة المرجعية\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eالكاميرا\u003c\/th\u003e\n\n\u003cth\u003eموصل 16 مسار MIPI CSI-2\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003ePCIe\u003c\/th\u003e\n\n\u003cth\u003eفتحة x16 PCIe تدعم x8 PCIe Gen4\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eRJ45\u003c\/th\u003e\n\n\u003cth\u003eحتى 10 جيجابت إيثرنت\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eM.2 Key M\u003c\/th\u003e\n\n\u003cth\u003ex4 PCIe Gen 4\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eM.2 Key E\u003c\/th\u003e\n\n\u003cth\u003ex1 PCIe Gen 4, USB 2.0, UART, I2S\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eUSB Type-C\u003c\/th\u003e\n\n\u003cth\u003e2x USB 3.2 Gen2 مع دعم USB-PD\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eUSB Type-A\u003c\/th\u003e\n\n\u003cth\u003e2x USB 3.2 Gen2, 2x USB 3.2 Gen1\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eUSB Micro-B\u003c\/th\u003e\n\n\u003cth\u003eUSB 2.0\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eDisplayPort\u003c\/th\u003e\n\n\u003cth\u003eDisplayPort 1.4a (+MST)\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eفتحة microSD\u003c\/th\u003e\n\n\u003cth\u003eبطاقات UHS-1 حتى وضع SDR104\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eأخرى\u003c\/th\u003e\n\n\u003cth\u003eرأس 40 سن (I2C, GPIO, SPI, CAN, I2S, UART, DMIC) \u003cbr\u003eرأس أتمتة 12 سن \u003cbr\u003eرأس لوحة صوت 10 سن \u003cbr\u003eرأس JTAG 10 سن \u003cbr\u003eرأس مروحة 4 سن \u003cbr\u003eموصل بطارية RTC احتياطي 2 سن \u003cbr\u003eمقبس طاقة تيار مستمر \u003cbr\u003eأزرار الطاقة، استعادة القوة، وإعادة الضبط\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth\u003eالأبعاد\u003c\/th\u003e\n\n\u003cth\u003e110 مم × 110 مم × 71.65 مم \u003cbr\u003e(الارتفاع يشمل الأقدام، اللوحة الحاملة، الوحدة، والحل الحراري)\u003c\/th\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/thead\u003e\n\n\n\u003c\/table\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e","brand":"NVIDIA","offers":[{"title":"Default Title","offer_id":39806068162646,"sku":"SBC1105-DEV","price":424999.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/products\/agx-drive-concord-2c50-P_2x_f70ef5ff-e87e-46c6-8c9f-2abfc3138002.png?v=1650646505"},{"product_id":"jetson-nano-compact-deploy-kit-online","title":"مجموعة تطوير ThinkRobotics Jetson Nano المدمجة (B01 - 4 جيجابايت)","description":"\u003ch2 style=\"text-align: center;\"\u003e\u003cspan data-sheets-userformat='{\"2\":707,\"3\":{\"1\":0},\"4\":{\"1\":2,\"2\":16777215},\"9\":1,\"10\":1,\"12\":0}' data-sheets-value='{\"1\":2,\"2\":\"SBC1023\"}' data-mce-fragment=\"1\"\u003eمجموعة تطوير ThinkRobotics NVIDIA Jetson Nano\u003c\/span\u003e\u003c\/h2\u003e\n\u003cp\u003eأصبحت قوة الذكاء الاصطناعي الحديث متاحة الآن للمبتكرين والدارسين ومطوري الأنظمة المدمجة في كل مكان.\u003c\/p\u003e\n\u003cp\u003eتعد مجموعة تطوير NVIDIA\u003csup\u003e®\u003c\/sup\u003e Jetson Nano\u003csup\u003e™\u003c\/sup\u003e حاسوباً صغيراً وقوياً يتيح لك تشغيل شبكات عصبية متعددة بالتوازي لتطبيقات مثل تصنيف الصور، واكتشاف الأشياء، والتجزئة، ومعالجة الكلام. كل ذلك في منصة سهلة الاستخدام تعمل بطاقة لا تتجاوز 5 واط.\u003c\/p\u003e\n\u003cp\u003eنظراً لعدم توفر مجموعات تطوير NVIDIA Jetson الأصلية، تقدم لكم ThinkRobotics مجموعة تطوير Nano مخصصة، تتكون من المكونات التالية:\u003cbr\u003e\u003c\/p\u003e\n\u003cul\u003e\n\n\u003cli\u003e\u003ca href=\"https:\/\/thinkrobotics.in\/products\/weact-studio-tx2-nx-carrier-board?_pos=2\u0026amp;_psq=weact\u0026amp;_ss=e\u0026amp;_v=1.0\" target=\"_blank\"\u003eلوحة الناقل WeAct\u003c\/a\u003e\u003c\/li\u003e\n\n\u003cli\u003e\u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-nano-module?_pos=2\u0026amp;_psq=jetson%20nano\u0026amp;_ss=e\u0026amp;_v=1.0\" target=\"_blank\"\u003eوحدة Jetson Nano\u003c\/a\u003e\u003c\/li\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/thinkrobotics.in\/products\/jetson-nano-heatsink?_pos=2\u0026amp;_psq=nano%20heat%20\u0026amp;_ss=e\u0026amp;_v=1.0\"\u003eمشتت حراري لـ Jetson Nano\u003c\/a\u003e \u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eابدأ اليوم مع مجموعة تطوير Jetson Nano، المحملة بنظام Ubuntu، فهذه المجموعات جاهزة للاستخدام بمجرد إخراجها من الصندوق.\u003c\/strong\u003e\u003c\/p\u003e\n\u003ch4\u003e\u003cspan style=\"color: #ff2a00;\"\u003e\u003cstrong\u003eيتوفر خصم على الكميات الكبيرة. اتصل بنا لخدمات تحميل نظام التشغيل والبرمجة النصية المخصصة لوحدة Nano. يمكننا تجهيزها للعمل بالذكاء الاصطناعي من أجلك.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/h4\u003e\n\u003cp\u003e\u003cstrong\u003eيتم شحن جميع مجموعات Jetson مجاناً عبر Bluedart (ينطبق هذا على مناطق خدمة Bluedart فقط).\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eتلبي لوحة الناقل من WeAct Studio المتطلبات المحددة لوحدات Xavier NX وTX2 NX وNano، بما في ذلك نطاق دخل الجهد الواسع، ومجموعة متنوعة من الواجهات، واستهلاك الطاقة المنخفض، وحماية الطاقة، ومجموعة من الميزات الأخرى.\u003c\/p\u003e\n\u003cul\u003e\n\n\u003cli\u003eمناسبة لوحدات NVIDIA Jetson Nano وXavier NX وTX2 NX\u003c\/li\u003e\n\n\u003cli\u003eجهد الدخل: 7 فولت ~ 26 فولت\u003c\/li\u003e\n\n\u003cli\u003eأقصى استهلاك للطاقة: 25 واط\u003c\/li\u003e\n\n\u003cli\u003eدرجة حرارة التشغيل: 0 درجة مئوية ~ 70\u003cmeta charset=\"UTF-8\"\u003e \u003cspan data-mce-fragment=\"1\"\u003eدرجة مئوية\u003c\/span\u003e\n\n\u003c\/li\u003e\n\n\u003cli\u003eالحجم: 90 مم × 60 مم × 24 مم\u003c\/li\u003e\n\n\u003cli\u003eالوزن: 58 جم\u003c\/li\u003e\n\n\u003cli\u003eالواجهات: USB3.0 ×2، USB2.0 ×2، USB_OTG ×1، MicroSD ×1، MiniPCIE ×1، HDMI ×1، CAN ×1 (لـ Xavier NX وTX2 NX)، MIPI CSI ×2، Giga Ethernet ×1، 3.3V UART ×2، 3v3 GPIO ×2\u003c\/li\u003e\n\n\u003cli\u003eوظائف إضافية:\u003c\/li\u003e\n\n\u003cul\u003e\n\n\u003cli\u003eتدعم الإقلاع التلقائي \/ وضع السكون \/ إيقاف التشغيل عند الضغط المطول\u003c\/li\u003e\n\n\u003cli\u003eتدعم حماية OPP \/ OVP \/ OCP\u003c\/li\u003e\n\n\u003cli\u003eتدعم حماية طاقة الأجهزة الطرفية \/ حماية كاملة للواجهات من التفريغ الكهروستاتيكي (ESD)\u003c\/li\u003e\n\n\u003cli\u003eدائرة تفريغ\u003c\/li\u003e\n\n\u003cli\u003eتدعم بطاقات الشبكة اللاسلكية WiFi \/ 4G التي تعمل عبر PCIe المدمج\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003cli\u003eدليل المستخدم متاح على \u003ca href=\"https:\/\/github.com\/WeActTC\/Nano_TX2-Xavier_NX-CB\" target=\"_blank\"\u003e\u003cspan data-mce-fragment=\"1\"\u003e\u003cstrong data-spm-anchor-id=\"a2g0o.detail.1000023.i0.3e8b610c9PvGvV\" data-mce-fragment=\"1\"\u003ehttps:\/\/github.com\/WeActTC\/Nano_TX2-Xavier_NX-CB\u003c\/strong\u003e\u003c\/span\u003e\u003c\/a\u003e\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003cdiv style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/H2cd7979d19884a5daacf8adfcd792400R.jpg?v=1641315440\" alt=\"\"\u003e\u003c\/div\u003e","brand":"ThinkRobotics","offers":[{"title":"Default Title","offer_id":39902193746006,"sku":"SBC1023","price":28999.99,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/products\/SBC1023-1.png?v=1654827854"},{"product_id":"nvidia-jetson-nano-developer-kit-online-b01-4gb","title":"مجموعة نشر Jetson Nano من ThinkRobotics (إصدار B01 - سعة 4 جيجابايت)","description":"\u003cp\u003e\u003cmeta charset=\"UTF-8\"\u003e\u003cstrong\u003eتأتي مجموعة تطوير ThinkRobotics NVIDIA Jetson Nano (سعة 4 جيجابايت) مزودة بلوحة حاملة غنية بالواجهات من SEEED studio، مع تثبيت مسبق لنظام Jetpack.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eتُعد اللوحة الحاملة J101 لوحة حاملة فعالة من حيث التكلفة وغنية بالواجهات ومتوافقة مع NVIDIA Jetson Nano. وهي تتضمن واجهة HDMI 2.0، ومنفذي USB 2.0، ومنفذ USB 3.0 واحد، وفتحة لبطاقة micro SD، ومنفذي 2 xCSI، وواجهة M.2 key E لشبكات WIFI \/ BT، وواجهات GPIO وI2C وI2S، ومروحة، وغيرها من الواجهات الطرفية الغنية. وتتمتع بتصميم وظيفي مشابه تقريبًا وبنفس حجم اللوحة الحاملة لجهاز NVIDIA® Jetson Nano™ B01 تماماً.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan style=\"color: #ff2a00;\"\u003e\u003cstrong\u003eقد يختلف لون الهيكل.\u003c\/strong\u003e لتخصيص الهيكل المطبوع ثلاثي الأبعاد والبرمجة، يرجى التواصل معنا. تأتي اللوحة الحاملة والوحدات مع ضمان محدود من الشركة المصنعة لمدة عام واحد بدعم من ThinkRobotics.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eملاحظة: وحدة تزويد الطاقة غير مدرجة في المجموعة ويجب شراؤها بشكل منفصل.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan style=\"color: #2b00ff;\"\u003e\u003cstrong\u003eتتوفر أكثر من 100 وحدة. عادة ما يتم الشحن خلال 3 أيام عمل.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan style=\"color: #085d87;\"\u003e\u003cstrong\u003eالتوثيق والويكي:\u003c\/strong\u003e يرجى أيضاً الاطلاع على \u003cem\u003e\u003cstrong\u003e\u003ca href=\"https:\/\/wiki.seeedstudio.com\/reComputer_Jetson_Series_Started_Guide\/\" style=\"color: #085d87; text-decoration: underline;\" target=\"_blank\"\u003eدليل ويكي Seeed\u003c\/a\u003e\u003c\/strong\u003e\u003c\/em\u003e الذي يتضمن كيفية البدء باستخدام Jetson Nano وكذلك بناء مشاريع مختلفة.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eالمميزات\u003c\/h3\u003e\n\u003cdiv\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003cul\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eمناسبة تماماً: صُممت خصيصاً لوحدة \u003cstrong\u003eJetson Nano Module\u003c\/strong\u003e (260-سن SODIMM).\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\n\n\u003cstrong\u003eبديل للوحة حاملة مجموعة التطوير\u003c\/strong\u003e: تطابق في الحجم بنسبة 1:1 وتتمتع بتصميم وظيفي مشابه تقريباً للوحة الحاملة الخاصة بمجموعة تطوير نانو الرسمية من Nvidia.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\n\n\u003cstrong\u003eتخزين قابل للتوسيع\u003c\/strong\u003e: فتحة بطاقة SD لتوسيع سعة تخزين وحدة نانو (16 جيجابايت eMMC).\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\n\n\u003cstrong\u003eأجهزة طرفية غنية\u003c\/strong\u003e: استقرار أداء أعلى يتضمن منافذ USB 3.0 وUSB 2.0، وواجهة M.2 key E لـ WIFI، وRTC، ومنفذ Raspberry Pi GPIO بـ 40 سناً، وما إلى ذلك.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\n\n\u003cstrong\u003eعالية الفعالية من حيث التكلفة\u003c\/strong\u003e: مناسبة للبداية الجيدة والتقييم السريع لتطبيقات الذكاء الاصطناعي.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eتأتي بهيكل مطبوع ثلاثي الأبعاد كخيار اختياري.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eشهادات شاملة: FCC، CE، RoHS، KC.\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003cp\u003e\u003cimg class=\"lazy\" width=\"960\" height=\"960\" data-src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/carrier_board\/J101boardspec.png\" src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/carrier_board\/J101boardspec.png\"\u003e\u003c\/p\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003ch3 class=\"p\"\u003eالوظائف\u003c\/h3\u003e\n\n\u003cp class=\"p\"\u003eبالعمل مع وحدة NVIDIA Jetson Nano، التي تعمل بمعالج NVIDIA Maxwell مع 128 نواة NVIDIA CUDA®، فهي جاهزة لجلب قوة الذكاء الاصطناعي الحديث للجميع: من صناع ومتعلمين ومطوري الأنظمة المدمجة.\u003c\/p\u003e\n\n\u003cp class=\"p\"\u003eمع تجميع وحدة NVIDIA Jetson Nano، يمكنها دعم \u003cstrong\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetpack\"\u003eNVIDIA JetPack\u003c\/a\u003e\u003c\/strong\u003e، الذي يتضمن حزمة دعم اللوحة (BSP)، ونظام تشغيل Linux، ومكتبات برمجيات NVIDIA CUDA® وcuDNN وTensorRT™ للتعلم العميق، ورؤية الحاسوب، وحوسبة GPU، ومعالجة الوسائط المتعددة، وغير ذلك الكثير. بفضل موصلات الكاميرا المتعددة، فهي مناسبة لتشغيل شبكات عصبية متعددة بالتوازي لتطبيقات مثل تصنيف الصور، واكتشاف الأشياء، والتجزئة، ومعالجة الكلام.\u003c\/p\u003e\n\n\u003ch2 dir=\"ltr\"\u003eتطبيقات الذكاء الاصطناعي المتطورة (Edge AI)\u003c\/h2\u003e\n\n\u003cp dir=\"ltr\"\u003eبالعمل مع وحدة Jetson Nano، فإن reComputer J101 جاهزة لجلب قوة الذكاء الاصطناعي الحديثة إلى تطبيقات العالم الحقيقي مثل التعرف على الصور، واكتشاف الأشياء، وتقدير الوضعية، ومعالجة الفيديو، وغيرها الكثير. تحقق من أمثلة التطبيقات التالية مع البرامج التعليمية!\u003c\/p\u003e\n\n\u003cul\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.edgeimpulse.com\/blog\/recognizing-your-blind-spots-pedestrian-detection-system-with-nvidia-jetson-nano\" target=\"_blank\"\u003eاكتشاف المشاة بواسطة Edge Impulse\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/03\/03\/deploy-hard-hat-detection-for-enforcing-workplace-safety\/\" target=\"_blank\"\u003eاكتشاف خوذة الأمان\u003c\/a\u003e وبناء نظام مخصص لاكتشاف معدات الوقاية الشخصية (PPE)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/alwaysai.co\/blog\/using-pose-estimation-on-the-jetson-nano-with-alwaysai\" target=\"_blank\"\u003eتقدير الوضعية باستخدام alwaysAI\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/gtc\/2020\/video\/s22675-vid\" target=\"_blank\"\u003eاكتشاف الشذوذ البصري باستخدام NVIDIA Deepstream IoT\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/06\/08\/retail-store-items-detection-using-yolov5-roboflow-and-node-red\/\" target=\"_blank\"\u003eاكتشاف سلع متاجر التجزئة\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eاكتشاف حرائق الغابات\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eاكتشاف الحيوانات\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003cp dir=\"ltr\"\u003eيمكنك العثور في صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/community\/resources\" target=\"_blank\"\u003eموارد مجتمع Jetson\u003c\/a\u003e على أدوات ودروس تعليمية أنشأها المجتمع لتعزيز خبرتك في التطوير، واطلع على صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/community\/jetson-projects\" target=\"_blank\"\u003eمشاريع المجتمع\u003c\/a\u003e لإلهام مشروعك القادم!\u003c\/p\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch3\u003eالمواصفات:\u003c\/h3\u003e\n\n\u003cdiv\u003e\n\n\u003cul\u003e\n\n\u003cli\u003eتوافق الوحدة: \u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-nano-module?_pos=2\u0026amp;_sid=d0c5055a4\u0026amp;_ss=r\" target=\"_blank\"\u003eسلسلة Jetson Nano\u003c\/a\u003e\n\u003c\/li\u003e\n\n\u003cli\u003eحجم اللوحة المطبوعة PCB \/ الحجم الكلي: 100 مم X 80 مم\u003c\/li\u003e\n\n\u003cli\u003eالشاشة: منفذ HDMI واحد ومنفذ DP واحد\u003c\/li\u003e\n\n\u003cli\u003eكاميرا CSI: 2\u003c\/li\u003e\n\n\u003cli\u003eإيثرنت: منفذ جيجابت إيثرنت واحد (10\/100\/1000M)\u003c\/li\u003e\n\n\u003cli\u003eUSB: منفذ USB من النوع C واحد (مدخل طاقة)؛ منفذ USB 3.0 من النوع A واحد (5 جيجابت في الثانية)؛ منفذان USB 2.0 من النوع A؛ منفذ USB من النوع C واحد (وضع الجهاز)\u003c\/li\u003e\n\n\u003cli\u003eبطاقة Micro SD: فتحة بطاقة Micro SD واحدة (تردد ساعة 48 ميجاهرتز)\u003cbr\u003e\n\n\u003c\/li\u003e\n\n\u003cli\u003eواجهة M.2 Key E\u003c\/li\u003e\n\n\u003cli\u003eالمروحة: موصل مروحة واحد\u003c\/li\u003e\n\n\u003cli\u003eمنفذ متعدد الوظائف: منفذ 40-سن واحد، منفذ 12-سن واحد\u003c\/li\u003e\n\n\u003cli\u003eRTC: منفذ RTC بـ سنين، مقبس RTC (محجوز)\u003c\/li\u003e\n\n\u003cli\u003eمزود الطاقة: \u003ca href=\"https:\/\/thinkrobotics.in\/products\/20w-5v-4a-power-supply-for-nvidia-jetson-nano?_pos=2\u0026amp;_psq=usb+power+supply\u0026amp;_ss=e\u0026amp;_v=1.0\u0026amp;variant=39626382016598\" target=\"_blank\"\u003e5 فولت\/4 أمبير (USB من النوع C)\u003c\/a\u003e\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003ch3\u003eمقارنة مع اللوحة الحاملة لمجموعات تطوير سلسلة NVIDIA Nano:\u003c\/h3\u003e\n\n\u003cp\u003e\u003cimg src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/J101v2.png\" data-src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/J101v2.png\" height=\"auto\" width=\"auto\" class=\"lazy\"\u003e\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e","brand":"ThinkRobotics","offers":[{"title":"Without Case","offer_id":40058803585110,"sku":"SBC2067-NoC","price":34299.99,"currency_code":"INR","in_stock":false},{"title":"With 3D Printed Case","offer_id":40058803617878,"sku":"SBC2067-3D","price":34999.99,"currency_code":"INR","in_stock":false},{"title":"With 3D Printed Case for High Temp Applications","offer_id":40058803650646,"sku":"SBC2067-HT","price":35999.99,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/products\/SBC2067-4.png?v=1661936011"},{"product_id":"nvidia-jetson-xavier-nx-developer-kit-online","title":"مجموعة تطوير NVIDIA Jetson Xavier NX من ThinkRobotics - مدمجة","description":"\u003cp\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cmeta charset=\"utf-8\"\u003e\u003cstrong\u003eتأتي مجموعة تطوير ThinkRobotics NVIDIA Jetson Xavier NX مع لوحة حاملة غنية بالواجهات من SEEED studio، ونظام Jetpack مثبت مسبقًا.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eتتمتع اللوحة الحاملة reComputer J202 بتصميم ووظائف تكاد تطابق اللوحة الحاملة لـ NVIDIA® Jetson Xavier NX™، وتعمل بشكل مثالي مع وحدة Jetson Nano\/Xavier NX، وتتكون من منافذ USB 3.2 gen 2 (عدد 4)، وM.2 key E لشبكة WIFI، وM.2 Key M لأقراص SSD، وRTC، وCAN، ومنفذ GPIO بـ 40 سنًا لجهاز Raspberry Pi، وغيرها.\u003cbr\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eيمكن للوحة الحاملة العمل كبديل للوحة الحاملة لمجموعة تطوير NVIDIA Jetson Xavier NX، مما يسرع من عملية تطوير ونشر تطبيقات الذكاء الاصطناعي القادمة.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan style=\"color: #ff2a00;\"\u003eملاحظة: قد يختلف وقت التوصيل بين 7 إلى 10 أيام عمل. من أجل التجميع والبرمجة وتصميم الهيكل، يرجى التواصل معنا.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan style=\"color: #ff2a00;\"\u003e\u003cmeta charset=\"utf-8\"\u003e \u003cspan\u003eتأتي اللوحة الحاملة والوحدات مع ضمان محدود من الشركة المصنعة لمدة عام واحد مدعوم من قبل ThinkRobotics.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cem\u003e\u003cspan style=\"color: #000000;\"\u003eيمكن العثور على ورقة البيانات الخاصة باللوحة الحاملة J202 \u003ca href=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/reComputer-J202-carrier-board-datasheet.pdf\" target=\"_blank\"\u003eهنا\u003c\/a\u003e!\u003c\/span\u003e\u003c\/em\u003e\u003c\/p\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan style=\"color: #000000;\"\u003eتتضمن الحزمة:\u003c\/span\u003e\u003c\/h3\u003e\n\u003cul\u003e\n\n\u003cli\u003eلوحة حاملة J202\u003c\/li\u003e\n\n\u003cli\u003eوحدة Xavier NX\u003c\/li\u003e\n\n\u003cli\u003eمشتت حراري نشط\u003c\/li\u003e\n\n\u003cli\u003eNVMe (اختياري)\u003c\/li\u003e\n\n\u003cli\u003eمزود طاقة 12 فولت \/ 5 أمبير\u003c\/li\u003e\n\n\u003cli\u003eهيكل مطبوع بتقنية ثلاثية الأبعاد (PLA أو CF PETG)\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eالمميزات\u003c\/h3\u003e\n\u003cdiv\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003cul\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eملائمة تمامًا: مصممة لوحدة \u003cstrong\u003eJetson Nano\/Xavier NX\u003c\/strong\u003e (بمقاس 260 سن SODIMM).\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\n\n\u003cstrong\u003eبديل للوحة حاملة مجموعة التطوير\u003c\/strong\u003e: مطابقة بنسبة 1:1 في الحجم وتصميم وظيفي يكاد يطابق اللوحة الحاملة لمجموعة تطوير Nvidia الرسمية Jetson Xavier NX.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\n\n\u003cstrong\u003eأجهزة طرفية غنية\u003c\/strong\u003e: استقرار أعلى في الأداء يشمل منافذ USB 3.2 gen 2 (عدد 4)، وM.2 key E لشبكة WIFI، وM.2 Key M لأقراص SSD، وRTC، وCAN، ومنفذ GPIO بـ 40 سنًا لجهاز Raspberry Pi، وغيرها.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\n\n\u003cstrong\u003eتنوع عالٍ\u003c\/strong\u003e: مناسبة لتطبيقات الذكاء الاصطناعي الرسومية المعقدة.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eشهادات شاملة: FCC، CE، RoHS، KC\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\u003cimg src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/carrier_board\/J202boardspec.png\" height=\"1200\" width=\"1200\" class=\"lazy\"\u003e\u003c\/h2\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003cdiv\u003e\n\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eالوصف\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003cp class=\"p\"\u003ereComputer J202 هي لوحة حاملة متوافقة مع NVIDIA Jetson Nano \/ Xavier NX ذات أداء عالٍ وغنية بالواجهات، توفر \u003cstrong\u003eHDMI 2.0، وGigabit Ethernet، وUSB3.1 Gen 2، وM.2 key E للواي فاي\/البلوتوث، وM.2 key M، وكاميرا CSI، وCAN، وGPIO، وI2C، وI2S، ومروحة\u003c\/strong\u003e، وغيرها من الواجهات الطرفية الغنية. تتمتع بنفس التصميم الوظيفي والحجم للوحة الحاملة الخاصة بـ \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetson-xavier-nx-devkit\" target=\"_blank\"\u003e\u003cspan\u003e\u003cspan class=\"15\"\u003eNVIDIA® Jetson Xavier™\u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003e\u003cspan class=\"15\"\u003e \u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003cspan\u003e\u003cspan class=\"15\"\u003eNX DEVELOPER KIT\u003c\/span\u003e\u003c\/span\u003e. \u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch3 class=\"p\"\u003eالوظائف\u003c\/h3\u003e\n\n\u003cp class=\"p\"\u003eمع تجميع وحدة NVIDIA Jetson، يمكنها دعم \u003cstrong\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetpack\"\u003eNVIDIA JetPack\u003c\/a\u003e\u003c\/strong\u003e، الذي يتضمن حزمة دعم اللوحة (BSP)، ونظام التشغيل Linux، ومكتبات برمجيات NVIDIA CUDA®، وcuDNN، وTensorRT™ للتعلم العميق، ورؤية الحاسوب، وحوسبة GPU، ومعالجة الوسائط المتعددة، وغير ذلك الكثير.\u003c\/p\u003e\n\n\u003cp class=\"p\"\u003eبفضل موصلات الكاميرا المتعددة، فهي مناسبة لتشغيل شبكات عصبية متعددة بالتوازي لتطبيقات مثل تصنيف الصور، واكتشاف الأشياء، والتجزئة، ومعالجة الكلام. \u003c\/p\u003e\n\n\u003ch3\u003eالمواصفات:\u003c\/h3\u003e\n\n\u003cdiv\u003e\n\n\u003cul\u003e\n\n\u003cli\u003eتوافق الوحدة: \u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-nano-module?_pos=2\u0026amp;_psq=jetson%20nano\u0026amp;_ss=e\u0026amp;_v=1.0\" target=\"_blank\"\u003eJetson™ Nano\u003c\/a\u003e\/ \u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-xavier-nx-module?_pos=1\u0026amp;_psq=xavier%20nx\u0026amp;_ss=e\u0026amp;_v=1.0\" target=\"_blank\"\u003eXavier NX\u003c\/a\u003e\n\n\u003c\/li\u003e\n\n\u003cli\u003eحجم لوحة الدائرة المطبوعة (PCB) \/ الحجم الإجمالي: 100 مم X 80 مم\u003c\/li\u003e\n\n\u003cli\u003eشاشة العرض: 1x HDMI و 1x DP\u003c\/li\u003e\n\n\u003cli\u003eكاميرا CSI: 2\u003c\/li\u003e\n\n\u003cli\u003eإيثرنت: 1x Gigabit Ethernet (10\/100\/1000M)\u003c\/li\u003e\n\n\u003cli\u003eUSB: 4x USB 3.1 Type-A (10 جيجابت في الثانية لـ NX، 5 جيجابت في الثانية لـ Nano)؛ 1x USB Type-C (وضع الجهاز)\u003c\/li\u003e\n\n\u003cli\u003e1x M.2 Key E، 1x M.2 Key M\u003cbr\u003e\n\n\u003c\/li\u003e\n\n\u003cli\u003eمروحة: 1x موصل مروحة\u003c\/li\u003e\n\n\u003cli\u003e1x CAN\u003c\/li\u003e\n\n\u003cli\u003eمنفذ متعدد الوظائف: 1x 40-Pin، 1x 12-Pin\u003c\/li\u003e\n\n\u003cli\u003eRTC: 2-pin RTC، مقبس RTC (محجوز)\u003c\/li\u003e\n\n\u003cli\u003eمزود الطاقة: 12 فولت\/5 أمبير (مقبس برميلي 5.5\/2.1 مم)\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\n\u003c\/div\u003e\n\n\u003cp class=\"p\"\u003e \u003c\/p\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003ch2 dir=\"ltr\"\u003eتطبيقات الحوسبة الطرفية للذكاء الاصطناعي (Edge AI)\u003c\/h2\u003e\n\n\u003cp dir=\"ltr\"\u003eتعمل بأداء ذكاء اصطناعي يصل إلى 21 TOPS توفره Jetson Xavier NX، مما يوفر القدرة على تطوير واختبار حلول ذكية موفرة للطاقة وصغيرة الحجم مع استنتاج ذكاء اصطناعي دقيق ومتعدد الوسائط عبر مختلف الصناعات.\u003c\/p\u003e\n\n\u003cul\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.edgeimpulse.com\/blog\/recognizing-your-blind-spots-pedestrian-detection-system-with-nvidia-jetson-nano\" target=\"_blank\"\u003eاكتشاف المشاة بواسطة Edge Impulse\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/03\/03\/deploy-hard-hat-detection-for-enforcing-workplace-safety\/\" target=\"_blank\"\u003eاكتشاف الخوذات الصلبة\u003c\/a\u003e وبناء نظام مخصص لاكتشاف معدات الوقاية الشخصية (PPE)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/alwaysai.co\/blog\/using-pose-estimation-on-the-jetson-nano-with-alwaysai\" target=\"_blank\"\u003eتقدير الوضعية (Pose Estimation) مع alwaysAI\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/gtc\/2020\/video\/s22675-vid\" target=\"_blank\"\u003eاكتشاف الشذوذ المرئي باستخدام NVIDIA Deepstream IoT\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/06\/08\/retail-store-items-detection-using-yolov5-roboflow-and-node-red\/\" target=\"_blank\"\u003eاكتشاف أصناف متاجر التجزئة\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eاكتشاف حرائق الغابات\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eاكتشاف الحيوانات\u003c\/a\u003e \u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003cp dir=\"ltr\"\u003eاعثر في صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/community\/resources\" target=\"_blank\"\u003eموارد مجتمع Jetson\u003c\/a\u003e على الأدوات والبرامج التعليمية التي أنشأها المجتمع لتعزيز تجربتك في التطوير، وتحقق من صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/community\/jetson-projects\" target=\"_blank\"\u003eمشاريع المجتمع\u003c\/a\u003e لإلهام مشروعك القادم! \u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv\u003eيرجى أيضًا الاطلاع على \u003ca href=\"https:\/\/wiki.seeedstudio.com\/reComputer_Jetson_Series_Started_Guide\/\" target=\"_blank\"\u003e\u003cstrong\u003eدليل Seeed wiki\u003c\/strong\u003e\u003c\/a\u003e الذي يتضمن كيفية البدء مع Jetson Nano وأيضًا بناء مشاريع مختلفة. \u003c\/div\u003e\n\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv\u003e\u003cimg class=\"lazy\" width=\"1200\" height=\"1200\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/102991695_2.jpg\"\u003e\u003c\/div\u003e\n\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv\u003e\n\n\u003cdiv\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eالمقارنة مع اللوحات الحاملة لمجموعة تطوير NVIDIA Xavier NX\u003c\/h3\u003e\n\n\u003cp\u003e\u003cimg class=\"lazy\" width=\"860\" height=\"860\" src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/J202carrierboard.png\"\u003e\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch3\u003e نظرة عامة على الأجهزة\u003c\/h3\u003e\n\n\u003cp\u003e\u003cimg src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20FRONT.png\" height=\"900\" width=\"900\" class=\"lazy\"\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003cimg src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20BACK.png\" height=\"860\" width=\"860\" class=\"lazy\"\u003e\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e","brand":"ThinkRobotics","offers":[{"title":"8GB \/ No SSD","offer_id":40045221707862,"sku":"SBC1025.1","price":90599.99,"currency_code":"INR","in_stock":true},{"title":"8GB \/ 240GB SSD","offer_id":40045221773398,"sku":"SBC1025.1+SBC2105.24","price":97999.99,"currency_code":"INR","in_stock":true},{"title":"8GB \/ 480GB SSD","offer_id":43952852697405,"sku":"SBC1025.1+SBC2105.48","price":100549.99,"currency_code":"INR","in_stock":true},{"title":"8GB \/ 960GB SSD","offer_id":43952852730173,"sku":"SBC1025.1+SBC2105.96","price":108199.99,"currency_code":"INR","in_stock":true},{"title":"16GB \/ No SSD","offer_id":40045267189846,"sku":"SBC1025.2","price":117999.99,"currency_code":"INR","in_stock":true},{"title":"16GB \/ 240GB SSD","offer_id":40045267222614,"sku":"SBC1025.2+SBC2105.24","price":125399.99,"currency_code":"INR","in_stock":true},{"title":"16GB \/ 480GB SSD","offer_id":43952852762941,"sku":"SBC1025.2+SBC2105.48","price":127949.99,"currency_code":"INR","in_stock":true},{"title":"16GB \/ 960GB SSD","offer_id":43952852795709,"sku":"SBC1025.2+SBC2105.96","price":135599.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/products\/XAVIERNX-2.png?v=1662619630"},{"product_id":"recomputer-j2012-j2021-edge-ai-device-with-jetson-xavier-nx-online","title":"جهاز ThinkRobotics Edge AI مزود بوحدة Jetson Xavier NX، وهيكل من الألومنيوم، ويعتمد على reComputer J2012 \/ J2021","description":"\u003ch2 style=\"text-align: center;\"\u003eجهاز حوسبة حافة ذكاء اصطناعي (Edge AI) مع وحدة Jetson Xavier NX\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eهيكل ألمنيوم | نظام Jetpack مثبت مسبقاً | reComputer J2012 \/ J2021\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cdiv style=\"text-align: left;\" class=\"document\"\u003e\n\n\u003cp style=\"text-align: center;\"\u003eبفضل وحدات التوسعة الغنية، والأجهزة الطرفية الصناعية، ونظام إدارة الحرارة، فإن reComputer المخصص لمنصة Jetson جاهز لمساعدتك على تسريع وتوسيع نطاق منتجات الذكاء الاصطناعي من الجيل التالي عبر نشر نماذج الشبكات العصبية العميقة (DNN) وأطر عمل تعلم الآلة (ML) على الحافة (Edge)، والقيام بعمليات الاستدلال بأداء عالٍ، وذلك لمهام مثل التصنيف في الوقت الفعلي، واكتشاف الأجسام، وتقدير الوضعية، والتقسيم الدلالي، ومعالجة اللغات الطبيعية (NLP).\u003c\/p\u003e\n\n\u003cp style=\"text-align: center;\"\u003eفي Seeed Studio، ستجد كل ما تحتاجه للعمل مع منصة NVIDIA Jetson – بدءاً من مجموعات تطوير NVIDIA Jetson الرسمية، ولوحات الناقل (carrier boards) التي صممتها Seeed، وأجهزة الحافة، بالإضافة إلى الملحقات.\u003c\/p\u003e\n\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\n\u003ch2 style=\"text-align: center;\" dir=\"ltr\"\u003eالميزات\u003c\/h2\u003e\n\n\u003ctable style=\"border-collapse: collapse; width: 95.3726%; margin-left: auto; margin-right: auto;\" height=\"396\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 10px; text-align: center; width: 100%;\"\u003e\n\n\u003cstrong\u003eجهاز حافة ذكاء اصطناعي بحجم كف اليد\u003c\/strong\u003e تم بناؤه باستخدام وحدة Jetson Xavier NX 16GB الإنتاجية، حيث يوفر 384 نواة NVIDIA CUDA® وأداء ذكاء اصطناعي يصل إلى 21 تريليون عملية في الثانية (TOPs)، مع عامل شكل مدمج بحجم 130 مم × 120 مم × 50 مم.\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 10px; text-align: center; width: 100%;\"\u003e\n\n\u003cstrong\u003eبديل لمجموعة تطوير NVIDIA Jetson Xavier NX:\u003c\/strong\u003e توفر لوحة الناقل منافذ إدخال\/إخراج غنية تتضمن منفذ Gigabit Ethernet، و4 منافذ USB 3.0 من النوع A، ومنفذ HDMI، ومنفذ DP.\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 10px; text-align: center; width: 100%;\"\u003e\n\n\u003cstrong\u003eنظام NVIDIA JetPack مثبت مسبقاً:\u003c\/strong\u003e يدعم حزمة برامج Jetson الكاملة وأدوات مطورين متنوعة من شركاء Seeed Edge AI، مما يتيح تطوير تطبيقات ذكاء اصطناعي سريعة وقوية للتصنيع، والخدمات اللوجستية، وتجارة التجزئة، والخدمات، والزراعة، والمدن الذكية، والرعاية الصحية، وعلوم الحياة.\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 10px; text-align: center; width: 100%;\"\u003e\n\n\u003cstrong\u003eتشغيل موفر للطاقة:\u003c\/strong\u003e يستهلك طاقة لا تتجاوز 10 وات مع توفير استدلال ذكاء اصطناعي عالي الأداء والدقة ومتعدد الوسائط على الحافة.\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 10px; text-align: center; width: 100%;\"\u003e\n\n\u003cstrong\u003eقابل للتوسعة:\u003c\/strong\u003e عبر الواجهات المدمجة وهيكل reComputer؛ ويدعم التثبيت على الحائط باستخدام فتحات التثبيت الموجودة في الخلف.\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\n\u003c\/div\u003e\n\u003cdiv\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003ch2 style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/carrier_board\/J202boardspec.png\" height=\"1200\" width=\"1200\" class=\"lazy\"\u003e\u003c\/h2\u003e\n\n\u003cdiv style=\"text-align: left;\" class=\"document\"\u003e\n\n\u003cdiv\u003e\n\n\u003cp class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e \u003c\/p\u003e\n\n\u003ch2 style=\"text-align: center;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eالوصف\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: left;\" class=\"document\"\u003e\n\n\u003cp style=\"text-align: center;\" class=\"p\"\u003ereComputer J202 هي لوحة ناقل (carrier board) عالية الأداء وغنية بالواجهات، ومتوافقة مع NVIDIA Jetson Nano \/ Xavier NX، وتوفر \u003cstrong\u003eHDMI 2.0، وGigabit Ethernet، وUSB3.1 Gen 2، وM.2 key E (لـ Wi-Fi \/ BT)، وM.2 key M، وكاميرا CSI، وCAN، وGPIO، وI2C، وI2S، ومروحة\u003c\/strong\u003e، وغيرها من الواجهات الطرفية الغنية. تتميز بنفس التصميم الوظيفي والحجم الخاص بلوحة الناقل لمجموعة تطوير \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetson-xavier-nx-devkit\" target=\"_blank\"\u003e\u003cspan\u003e\u003cspan class=\"15\"\u003eNVIDIA® Jetson Xavier™\u003c\/span\u003e\u003c\/span\u003e\u003cspan\u003e\u003cspan class=\"15\"\u003e \u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003cspan\u003e\u003cspan class=\"15\"\u003eNX DEVELOPER KIT\u003c\/span\u003e\u003c\/span\u003e.  \u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003cp style=\"text-align: left;\" class=\"p\"\u003e \u003c\/p\u003e\n\n\u003ch2 style=\"text-align: center;\" class=\"p\"\u003eالوظائف\u003c\/h2\u003e\n\n\u003cp style=\"text-align: center;\" class=\"p\"\u003eعند تجميع وحدة NVIDIA Jetson، يمكنها دعم \u003cstrong\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetpack\"\u003eNVIDIA JetPack\u003c\/a\u003e\u003c\/strong\u003e، الذي يتضمن حزمة دعم اللوحة (BSP)، ونظام تشغيل Linux، ومكتبات برمجيات NVIDIA CUDA® وcuDNN وTensorRT™ للتعلم العميق، ورؤية الحاسوب، وحوسبة GPU، ومعالجة الوسائط المتعددة، وغير ذلك الكثير.\u003c\/p\u003e\n\n\u003cp style=\"text-align: center;\" class=\"p\"\u003eبفضل موصلات الكاميرا المتعددة، تعد مناسبة لتشغيل شبكات عصبية متعددة بالتوازي لتطبيقات مثل تصنيف الصور، واكتشاف الأجسام، والتقسيم، ومعالجة الكلام. \u003c\/p\u003e\n\n\u003cp class=\"p\" style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\n\u003ch2 style=\"text-align: center;\"\u003eالمواصفات\u003c\/h2\u003e\n\n\u003ctable height=\"528\" style=\"border-collapse: collapse; width: 93.1517%; margin-left: auto; margin-right: auto;\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eتوافق الوحدة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003eXavier NX\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eحجم لوحة الدائرة (PCB) \/ الحجم الإجمالي\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e100 مم × 80 مم\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eالعرض\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e1 × HDMI، 1 × DP\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eكاميرا CSI\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e2\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eEthernet\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e1 × Gigabit Ethernet (10\/100\/1000 ميجابت)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eUSB\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e4 × USB 3.1 Type-A (10 جيجابت في الثانية لـ NX، 5 جيجابت في الثانية لـ Nano)\u003cbr\u003e1 × USB Type-C (وضع الجهاز)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eفتحات M.2\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e1 × M.2 Key E، 1 × M.2 Key M\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eالمروحة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e1 × موصل مروحة\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eCAN\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e1 × CAN\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eمنفذ متعدد الوظائف\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e1 × 40 سن، 1 × 12 سن\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eساعة الوقت الحقيقي (RTC)\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003eRTC بسنين، مقبس RTC (محجوز)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 51.6369%; text-align: center;\"\u003e\u003cstrong\u003eمصدر الطاقة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 48.3857%; text-align: center;\"\u003e12 فولت \/ 5 أمبير (مقبس برميلي 5.5 \/ 2.1 مم)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\u003cp class=\"p\"\u003e \u003c\/p\u003e\n\n\u003cdiv style=\"text-align: left;\" class=\"document\"\u003e\n\n\u003ch2 style=\"text-align: center;\" dir=\"ltr\"\u003eتطبيقات حوسبة حافة الذكاء الاصطناعي\u003c\/h2\u003e\n\n\u003cp style=\"text-align: center;\" dir=\"ltr\"\u003eمع أداء ذكاء اصطناعي يصل إلى 21 تريليون عملية في الثانية (TOPS) توفره وحدة Jetson Xavier NX، فإنه يوفر القدرة على تطوير واختبار حلول ذكية موفرة للطاقة وصغيرة الحجم مع استدلال ذكاء اصطناعي دقيق ومتعدد الوسائط عبر مختلف الصناعات.\u003c\/p\u003e\n\n\u003cul\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp style=\"text-align: center;\" dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.edgeimpulse.com\/blog\/recognizing-your-blind-spots-pedestrian-detection-system-with-nvidia-jetson-nano\" target=\"_blank\"\u003eاكتشاف المشاة بواسطة Edge Impulse\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli style=\"text-align: center;\" dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/03\/03\/deploy-hard-hat-detection-for-enforcing-workplace-safety\/\" target=\"_blank\"\u003eاكتشاف خوذات الأمان\u003c\/a\u003e وبناء نظام مخصص لاكتشاف معدات الوقاية الشخصية (PPE)\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli style=\"text-align: center;\" dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/alwaysai.co\/blog\/using-pose-estimation-on-the-jetson-nano-with-alwaysai\" target=\"_blank\"\u003eتقدير الوضعية مع alwaysAI\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli style=\"text-align: center;\" dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/gtc\/2020\/video\/s22675-vid\" target=\"_blank\"\u003eاكتشاف الشذوذ البصري باستخدام NVIDIA Deepstream IoT\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli style=\"text-align: center;\" dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/06\/08\/retail-store-items-detection-using-yolov5-roboflow-and-node-red\/\" target=\"_blank\"\u003eاكتشاف السلع في متاجر التجزئة\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli style=\"text-align: center;\" dir=\"ltr\"\u003e\n\n\u003cp dir=\"ltr\"\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eاكتشاف حرائق الغابات\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\"\u003e\n\n\u003cp style=\"text-align: center;\" dir=\"ltr\"\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eاكتشاف الحيوانات\u003c\/a\u003e \u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003cp style=\"text-align: center;\" dir=\"ltr\"\u003eتفضل بزيارة صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/community\/resources\" target=\"_blank\"\u003eموارد مجتمع Jetson\u003c\/a\u003e للعثور على الأدوات والبرامج التعليمية التي أنشأها المجتمع لتعزيز تجربة التطوير الخاصة بك، واطلع على صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/community\/jetson-projects\" target=\"_blank\"\u003eمشاريع المجتمع\u003c\/a\u003e لإلهام مشروعك القادم!\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: center;\"\u003eيرجى أيضاً الاطلاع على \u003ca href=\"https:\/\/wiki.seeedstudio.com\/reComputer_Jetson_Series_Started_Guide\/\" target=\"_blank\"\u003e\u003cstrong\u003eدليل Seeed wiki\u003c\/strong\u003e\u003c\/a\u003e الذي يتضمن كيفية البدء مع Jetson Nano وأيضاً بناء مشاريع مختلفة.\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: left;\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: left;\"\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" class=\"lazy\" width=\"1200\" height=\"1200\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/102991695_2.jpg\"\u003e\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: left;\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: left;\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: left;\"\u003e\n\n\u003cdiv\u003e\n\n\u003cdiv class=\"document\"\u003e\n\n\u003ch2 style=\"text-align: center;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eمقارنة مع لوحات الناقل الخاصة بمجموعة تطوير NVIDIA Xavier NX\u003c\/h2\u003e\n\n\u003cp\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" class=\"lazy\" width=\"860\" height=\"860\" src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/J202carrierboard.png\"\u003e\u003c\/p\u003e\n\n\u003cp\u003e \u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch2 style=\"text-align: center;\"\u003e نظرة عامة على الأجهزة\u003c\/h2\u003e\n\n\u003cp style=\"text-align: left;\"\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20FRONT.png\" height=\"900\" width=\"900\" class=\"lazy\"\u003e\u003c\/p\u003e\n\n\u003cp style=\"text-align: left;\"\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20BACK.png\" height=\"860\" width=\"860\" class=\"lazy\"\u003e\u003cbr\u003e\u003cbr\u003e\u003c\/p\u003e\n\n\u003ch2 style=\"text-align: center;\"\u003eقائمة الأجزاء (المجمعة)\u003c\/h2\u003e\n\n\u003ctable style=\"border-collapse: collapse; width: 93.3308%; height: 260px; margin-left: auto; margin-right: auto;\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr style=\"height: 19.5972px;\"\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 74.8658%; height: 19.5972px; text-align: center;\"\u003e\u003cstrong\u003eالعنصر\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 25.1582%; height: 19.5972px; text-align: center;\"\u003e\u003cstrong\u003eالكمية\u003c\/strong\u003e\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 39.1944px;\"\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 74.8658%; height: 39.1944px; text-align: center;\"\u003ereComputer J202 – لوحة ناقل لـ Jetson Nano وXavier NX مع 4 × USB 3.1، M.2 Key\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 25.1582%; height: 39.1944px; text-align: center;\"\u003e1\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 19.5972px;\"\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 74.8658%; height: 19.5972px; text-align: center;\"\u003eNvidia Jetson Xavier NX SOM (8 جيجابايت \/ 16 جيجابايت)\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 25.1582%; height: 19.5972px; text-align: center;\"\u003e1\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 19.5972px;\"\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 74.8658%; height: 19.5972px; text-align: center;\"\u003eقرص NVMe SSD سعة 240 جيجابايت\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 25.1582%; height: 19.5972px; text-align: center;\"\u003e1\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 19.5972px;\"\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 74.8658%; height: 19.5972px; text-align: center;\"\u003eمشتت حراري رسمي لـ Jetson Xavier NX مع مروحة\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 25.1582%; height: 19.5972px; text-align: center;\"\u003e1\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 19.5972px;\"\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 74.8658%; height: 19.5972px; text-align: center;\"\u003eمحول طاقة 12 فولت \/ 5 أمبير 60 وات\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 25.1582%; height: 19.5972px; text-align: center;\"\u003e1\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 19.5972px;\"\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 74.8658%; height: 19.5972px; text-align: center;\"\u003eهيكل re_computer – حاوية متوافقة للحواسيب أحادية اللوحة (SBCs) الشائعة\u003c\/td\u003e\n\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 25.1582%; height: 19.5972px; text-align: center;\"\u003e1\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\u003cp style=\"text-align: left;\"\u003e \u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e","brand":"Seeed Studio","offers":[{"title":"8GB","offer_id":40063820169302,"sku":"SBC2066-8","price":93899.99,"currency_code":"INR","in_stock":true},{"title":"16GB","offer_id":40063820202070,"sku":"SBC2066-16","price":121299.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/products\/110061363_feature-20_1.jpg?v=1663598507"},{"product_id":"advanced-thinkrobotics-nvidia-jetson-nano-development-kit-b01-4gb-online","title":"طقم تطوير ThinkRobotics المتطور بنظام NVIDIA Jetson Nano (إصدار B01-4GB)","description":"\u003cp bis_size='{\"x\":12,\"y\":16,\"w\":550,\"h\":0,\"abs_x\":570,\"abs_y\":317}'\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" data-mce-fragment=\"1\" bis_size='{\"x\":12,\"y\":16,\"w\":550,\"h\":58,\"abs_x\":570,\"abs_y\":317}'\u003e\u003cmeta charset=\"utf-8\"\u003e\u003cstrong data-mce-fragment=\"1\" bis_size='{\"x\":12,\"y\":17,\"w\":508,\"h\":56,\"abs_x\":570,\"abs_y\":318}'\u003eتأتي مجموعة تطوير Advanced ThinkRobotics NVIDIA Jetson Nano (4 جيجابايت) هذه مع لوحة حامل J202 غنية بالواجهات من SEEED studio، مع تثبيت مسبق لنظام Jetpack. \u003c\/strong\u003e\u003c\/p\u003e\n\u003cblockquote bis_size='{\"x\":52,\"y\":90,\"w\":470,\"h\":39,\"abs_x\":610,\"abs_y\":391}'\u003e\n\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" data-mce-fragment=\"1\" bis_size='{\"x\":52,\"y\":90,\"w\":470,\"h\":39,\"abs_x\":610,\"abs_y\":391}'\u003e\u003cspan style=\"color: #c20000;\" bis_size='{\"x\":52,\"y\":91,\"w\":426,\"h\":36,\"abs_x\":610,\"abs_y\":392}'\u003eهذا المنتج مصنع في الهند، مع نسبة تصنيع محلي تتجاوز 40%. \u003c\/span\u003e\u003c\/p\u003e\n\n\n\u003c\/blockquote\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" data-mce-fragment=\"1\" bis_size='{\"x\":12,\"y\":145,\"w\":550,\"h\":78,\"abs_x\":570,\"abs_y\":446}'\u003eتتمتع لوحة الحامل reComputer J202 بتصميم ووظائف تكاد تطابق لوحة حامل NVIDIA® Jetson Xavier NX™، وهي تعمل بشكل مثالي مع وحدة Jetson Nano\/Xavier NX، وتتكون من منافذ USB 3.2 gen 2 (عدد 4)، وموصل M.2 key E لشبكة الواي فاي، وموصل M.2 Key M لمحركات أقراص SSD، وRTC، وCAN، وموصل GPIO بـ 40 سنًا متوافق مع Raspberry Pi، وما إلى ذلك.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" data-mce-fragment=\"1\" bis_size='{\"x\":12,\"y\":240,\"w\":550,\"h\":39,\"abs_x\":570,\"abs_y\":541}'\u003eيمكن للوحة الحامل أن تعمل كبديل للوحة حامل مجموعة تطوير NVIDIA Jetson Xavier NX، مما يسرع من تطوير ونشر تطبيق الذكاء الاصطناعي التالي الخاص بك.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" data-mce-fragment=\"1\" bis_size='{\"x\":12,\"y\":295,\"w\":550,\"h\":39,\"abs_x\":570,\"abs_y\":596}'\u003e\u003cspan style=\"color: #ff2a00;\" bis_size='{\"x\":12,\"y\":296,\"w\":542,\"h\":36,\"abs_x\":570,\"abs_y\":597}'\u003eملاحظة: قد يتراوح وقت التسليم بين 7 إلى 10 أيام عمل. للتجميع والبرمجة وتصميم الصندوق، يرجى الاتصال بنا.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" data-mce-fragment=\"1\" bis_size='{\"x\":12,\"y\":350,\"w\":550,\"h\":39,\"abs_x\":570,\"abs_y\":651}'\u003e\u003cspan style=\"color: #ff2a00;\" bis_size='{\"x\":12,\"y\":351,\"w\":531,\"h\":36,\"abs_x\":570,\"abs_y\":652}'\u003e\u003cmeta charset=\"utf-8\"\u003e \u003cspan bis_size='{\"x\":12,\"y\":351,\"w\":531,\"h\":36,\"abs_x\":570,\"abs_y\":652}'\u003eتأتي لوحة الحامل والوحدات مع ضمان محدود من الشركة المصنعة لمدة عام واحد مدعوم من ThinkRobotics.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" data-mce-fragment=\"1\" bis_size='{\"x\":12,\"y\":405,\"w\":550,\"h\":19,\"abs_x\":570,\"abs_y\":706}'\u003e\u003cstrong bis_size='{\"x\":12,\"y\":406,\"w\":180,\"h\":17,\"abs_x\":570,\"abs_y\":707}'\u003e\u003cspan style=\"color: #000000;\" bis_size='{\"x\":12,\"y\":406,\"w\":180,\"h\":17,\"abs_x\":570,\"abs_y\":707}'\u003eيرجى ملاحظة خيارات الصندوق:\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul bis_size='{\"x\":12,\"y\":441,\"w\":550,\"h\":39,\"abs_x\":570,\"abs_y\":742}'\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":441,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":742}'\u003e\u003cspan style=\"color: #000000;\" bis_size='{\"x\":52,\"y\":442,\"w\":384,\"h\":17,\"abs_x\":610,\"abs_y\":743}'\u003eيأتي المشتت الحراري السلبي مع صندوق بلاستيكي مطبوع بتقنية ثلاثية الأبعاد (PLA)\u003c\/span\u003e\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":461,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":762}'\u003e\n\n\u003cspan style=\"color: #000000;\" bis_size='{\"x\":52,\"y\":462,\"w\":362,\"h\":17,\"abs_x\":610,\"abs_y\":763}'\u003eيأتي المشتت الحراري النشط مع صندوق مطبوع بتقنية ثلاثية الأبعاد من نايلون ألياف الكربون (CF Nylon)\u003c\/span\u003e\u003cbr bis_size='{\"x\":414,\"y\":462,\"w\":0,\"h\":17,\"abs_x\":972,\"abs_y\":763}'\u003e\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" bis_size='{\"x\":12,\"y\":494,\"w\":550,\"h\":22,\"abs_x\":570,\"abs_y\":795}'\u003eالمميزات\u003c\/h3\u003e\n\u003cdiv bis_size='{\"x\":12,\"y\":531,\"w\":550,\"h\":6592,\"abs_x\":570,\"abs_y\":832}'\u003e\n\n\u003cdiv class=\"document\" bis_size='{\"x\":12,\"y\":531,\"w\":550,\"h\":6592,\"abs_x\":570,\"abs_y\":832}'\u003e\n\n\u003cul bis_size='{\"x\":12,\"y\":531,\"w\":550,\"h\":176,\"abs_x\":570,\"abs_y\":832}'\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" bis_size='{\"x\":52,\"y\":531,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":832}'\u003eمناسبة تمامًا: مصممة لوحدات \u003cstrong bis_size='{\"x\":231,\"y\":532,\"w\":158,\"h\":17,\"abs_x\":789,\"abs_y\":833}'\u003eJetson Nano\/Xavier NX\u003c\/strong\u003e (260 سن SODIMM).\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" bis_size='{\"x\":52,\"y\":551,\"w\":510,\"h\":58,\"abs_x\":610,\"abs_y\":852}'\u003e\n\n\u003cstrong bis_size='{\"x\":52,\"y\":552,\"w\":263,\"h\":17,\"abs_x\":610,\"abs_y\":853}'\u003eبديل للوحة حامل مجموعة المطورين\u003c\/strong\u003e: تطابق الحجم بنسبة 1:1 وتتمتع بتصميم وظيفي يكاد يطابق لوحة الحامل الخاصة بمجموعة تطوير NVIDIA Jetson Xavier NX الرسمية. \u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" bis_size='{\"x\":52,\"y\":609,\"w\":510,\"h\":58,\"abs_x\":610,\"abs_y\":910}'\u003e\n\n\u003cstrong bis_size='{\"x\":52,\"y\":610,\"w\":112,\"h\":17,\"abs_x\":610,\"abs_y\":911}'\u003eأجهزة طرفية غنية\u003c\/strong\u003e: تتضمن ثباتًا في الأداء من خلال منافذ USB 3.2 gen 2 (عدد 4)، وموصل M.2 key E لشبكة الواي فاي، وموصل M.2 Key M لمحركات أقراص SSD، وRTC، وCAN، وموصل GPIO بـ 40 سنًا، وما إلى ذلك.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" bis_size='{\"x\":52,\"y\":668,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":969}'\u003e\n\n\u003cstrong bis_size='{\"x\":52,\"y\":669,\"w\":104,\"h\":17,\"abs_x\":610,\"abs_y\":970}'\u003eتنوع عالٍ\u003c\/strong\u003e: مناسبة لتطبيقات الذكاء الاصطناعي الرسومية المعقدة.\u003c\/li\u003e\n\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" bis_size='{\"x\":52,\"y\":688,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":989}'\u003eشهادات شاملة: FCC، CE، RoHS، KC\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" bis_size='{\"x\":12,\"y\":721,\"w\":550,\"h\":1223,\"abs_x\":570,\"abs_y\":1022}'\u003e\u003cimg class=\"lazy\" width=\"1200\" height=\"1200\" data-src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/carrier_board\/J202boardspec.png\" src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/carrier_board\/J202boardspec.png\" bis_size='{\"x\":12,\"y\":721,\"w\":1200,\"h\":1200,\"abs_x\":570,\"abs_y\":1022}' data-mce-src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/carrier_board\/J202boardspec.png\"\u003e\u003c\/h2\u003e\n\n\u003cdiv class=\"document\" bis_size='{\"x\":12,\"y\":1955,\"w\":550,\"h\":29,\"abs_x\":570,\"abs_y\":2256}'\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":1955,\"w\":550,\"h\":29,\"abs_x\":570,\"abs_y\":2256}'\u003e\n\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" bis_size='{\"x\":12,\"y\":1955,\"w\":550,\"h\":29,\"abs_x\":570,\"abs_y\":2256}'\u003eالوصف\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv class=\"document\" bis_size='{\"x\":12,\"y\":1995,\"w\":550,\"h\":97,\"abs_x\":570,\"abs_y\":2296}'\u003e\n\n\u003cp class=\"p\" bis_size='{\"x\":12,\"y\":1995,\"w\":550,\"h\":97,\"abs_x\":570,\"abs_y\":2296}'\u003ereComputer J202 هي لوحة حامل عالية الأداء ومتوافقة مع NVIDIA Jetson Nano \/ Xavier NX، وتوفر واجهات \u003cstrong bis_size='{\"x\":12,\"y\":2016,\"w\":543,\"h\":36,\"abs_x\":570,\"abs_y\":2317}'\u003eHDMI 2.0، وإيثرنت جيجابت، وUSB3.1 Gen 2، وواي فاي\/بلوتوث M.2 key E، وM.2 key M، وكاميرا CSI، وCAN، وGPIO، وI2C، وI2S، ومروحة\u003c\/strong\u003e، وغيرها من الواجهات الطرفية الغنية. وهي تتمتع بنفس التصميم الوظيفي والحجم الخاص بلوحة حامل \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetson-xavier-nx-devkit\" bis_size='{\"x\":70,\"y\":2075,\"w\":161,\"h\":17,\"abs_x\":628,\"abs_y\":2376}' data-mce-href=\"https:\/\/developer.nvidia.com\/embedded\/jetson-xavier-nx-devkit\" target=\"_blank\"\u003e\u003cspan data-style=\"text-decoration: underline;\" bis_size='{\"x\":70,\"y\":2075,\"w\":157,\"h\":17,\"abs_x\":628,\"abs_y\":2376}'\u003e\u003cspan class=\"15\" bis_size='{\"x\":70,\"y\":2075,\"w\":157,\"h\":17,\"abs_x\":628,\"abs_y\":2376}'\u003eNVIDIA® Jetson Xavier™\u003c\/span\u003e\u003c\/span\u003e\u003cspan data-style=\"text-decoration: underline;\" bis_size='{\"x\":227,\"y\":2075,\"w\":3,\"h\":17,\"abs_x\":785,\"abs_y\":2376}'\u003e\u003cspan class=\"15\" bis_size='{\"x\":227,\"y\":2075,\"w\":3,\"h\":17,\"abs_x\":785,\"abs_y\":2376}'\u003e \u003c\/span\u003e\u003c\/span\u003e\u003c\/a\u003e\u003cspan data-style=\"text-decoration: underline;\" bis_size='{\"x\":231,\"y\":2075,\"w\":127,\"h\":17,\"abs_x\":789,\"abs_y\":2376}'\u003e\u003cspan class=\"15\" bis_size='{\"x\":231,\"y\":2075,\"w\":127,\"h\":17,\"abs_x\":789,\"abs_y\":2376}'\u003eNX DEVELOPER KIT\u003c\/span\u003e\u003c\/span\u003e.  \u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch3 class=\"p\" bis_size='{\"x\":12,\"y\":2109,\"w\":550,\"h\":22,\"abs_x\":570,\"abs_y\":2410}'\u003eالوظائف\u003c\/h3\u003e\n\n\u003cp class=\"p\" bis_size='{\"x\":12,\"y\":2143,\"w\":550,\"h\":78,\"abs_x\":570,\"abs_y\":2444}'\u003eبعد تجميع وحدة NVIDIA Jetson، يمكنها دعم \u003cstrong bis_size='{\"x\":402,\"y\":2144,\"w\":108,\"h\":17,\"abs_x\":960,\"abs_y\":2445}'\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/jetpack\" bis_size='{\"x\":402,\"y\":2144,\"w\":108,\"h\":17,\"abs_x\":960,\"abs_y\":2445}' data-mce-href=\"https:\/\/developer.nvidia.com\/embedded\/jetpack\"\u003eNVIDIA JetPack\u003c\/a\u003e\u003c\/strong\u003e، الذي يتضمن حزمة دعم اللوحة (BSP)، ونظام تشغيل Linux، ومكتبات برمجيات NVIDIA CUDA® وcuDNN وTensorRT™ للتعلم العميق، ورؤية الكمبيوتر، وحوسبة وحدة معالجة الرسومات، ومعالجة الوسائط المتعددة، وغير ذلك الكثير.\u003c\/p\u003e\n\n\u003cp class=\"p\" bis_size='{\"x\":12,\"y\":2237,\"w\":550,\"h\":58,\"abs_x\":570,\"abs_y\":2538}'\u003eبفضل موصلات الكاميرا المتعددة، فهي مناسبة لتشغيل شبكات عصبية متعددة بالتوازي لتطبيقات مثل تصنيف الصور، واكتشاف الأشياء، والتجزئة، ومعالجة الكلام. \u003c\/p\u003e\n\n\u003ch3 bis_size='{\"x\":12,\"y\":2312,\"w\":550,\"h\":22,\"abs_x\":570,\"abs_y\":2613}'\u003eالمواصفات:\u003c\/h3\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":2349,\"w\":550,\"h\":254,\"abs_x\":570,\"abs_y\":2650}'\u003e\n\n\u003cul bis_size='{\"x\":12,\"y\":2349,\"w\":550,\"h\":254,\"abs_x\":570,\"abs_y\":2650}'\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2349,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2650}'\u003eتوافق الوحدة: \u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-nano-module?_pos=2\u0026amp;_psq=jetson%20nano\u0026amp;_ss=e\u0026amp;_v=1.0\" bis_size='{\"x\":196,\"y\":2350,\"w\":92,\"h\":17,\"abs_x\":754,\"abs_y\":2651}' target=\"_blank\"\u003eJetson™ Nano\u003c\/a\u003e\/ \u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-xavier-nx-module?_pos=1\u0026amp;_psq=xavier%20nx\u0026amp;_ss=e\u0026amp;_v=1.0\" bis_size='{\"x\":297,\"y\":2350,\"w\":63,\"h\":17,\"abs_x\":855,\"abs_y\":2651}' target=\"_blank\"\u003eXavier NX\u003c\/a\u003e\n\n\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2368,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2669}'\u003eحجم اللوحة المطبوعة (PCB) \/ الحجم الإجمالي: 100 مم × 80 مم\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2388,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2689}'\u003eالعرض: منفذ HDMI واحد ومنفذ DP واحد\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2408,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2709}'\u003eكاميرا CSI: عدد 2\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2427,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2728}'\u003eإيثرنت: منفذ إيثرنت جيجابت واحد (10\/100\/1000 ميجابت)\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2447,\"w\":510,\"h\":39,\"abs_x\":610,\"abs_y\":2748}'\u003eUSB: عدد 4 USB 3.1 Type-A (10 جيجابت في الثانية لـ NX، و5 جيجابت في الثانية لـ Nano)؛ منفذ USB Type-C واحد (وضع الجهاز)\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2486,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2787}'\u003eمنفذ M.2 Key E واحد، منفذ M.2 Key M واحد\u003cbr bis_size='{\"x\":225,\"y\":2487,\"w\":0,\"h\":17,\"abs_x\":783,\"abs_y\":2788}'\u003e\n\n\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2506,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2807}'\u003eمروحة: موصل مروحة واحد\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2525,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2826}'\u003eمنفذ CAN واحد\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2545,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2846}'\u003eمنفذ متعدد الوظائف: منفذ 40 سنًا، ومنفذ 12 سنًا\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2564,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2865}'\u003eRTC: منفذ RTC بـ سنين، ومقبس RTC (محجوز)\u003c\/li\u003e\n\n\u003cli bis_size='{\"x\":52,\"y\":2584,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":2885}'\u003eمزود الطاقة: 12 فولت\/6 أمبير (مقبس برميلي 5.5\/2.1 مم)\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\n\u003c\/div\u003e\n\n\u003cp class=\"p\" bis_size='{\"x\":12,\"y\":2618,\"w\":550,\"h\":19,\"abs_x\":570,\"abs_y\":2919}'\u003e \u003c\/p\u003e\n\n\u003cdiv class=\"document\" bis_size='{\"x\":12,\"y\":2653,\"w\":550,\"h\":422,\"abs_x\":570,\"abs_y\":2954}'\u003e\n\n\u003ch2 dir=\"ltr\" bis_size='{\"x\":12,\"y\":2653,\"w\":550,\"h\":29,\"abs_x\":570,\"abs_y\":2954}'\u003eتطبيقات الذكاء الاصطناعي للحافة (Edge AI)\u003c\/h2\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":12,\"y\":2693,\"w\":550,\"h\":58,\"abs_x\":570,\"abs_y\":2994}'\u003eمع أداء ذكاء اصطناعي يصل إلى 21 TOPS توفره Jetson Xavier NX، فإنها توفر القدرة على تطوير واختبار حلول ذكية موفرة للطاقة وصغيرة الحجم مع استنتاج ذكاء اصطناعي دقيق ومتعدد الوسائط عبر مختلف الصناعات.\u003c\/p\u003e\n\n\u003cul bis_size='{\"x\":12,\"y\":2768,\"w\":550,\"h\":233,\"abs_x\":570,\"abs_y\":3069}'\u003e\n\n\u003cli dir=\"ltr\" bis_size='{\"x\":52,\"y\":2768,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3069}'\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":52,\"y\":2768,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3069}'\u003e\u003ca href=\"https:\/\/www.edgeimpulse.com\/blog\/recognizing-your-blind-spots-pedestrian-detection-system-with-nvidia-jetson-nano\" bis_size='{\"x\":52,\"y\":2769,\"w\":244,\"h\":17,\"abs_x\":610,\"abs_y\":3070}' data-mce-href=\"https:\/\/www.edgeimpulse.com\/blog\/recognizing-your-blind-spots-pedestrian-detection-system-with-nvidia-jetson-nano\" target=\"_blank\"\u003eكشف المشاة بواسطة Edge Impulse\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\" bis_size='{\"x\":52,\"y\":2803,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3104}'\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":52,\"y\":2803,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3104}'\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/03\/03\/deploy-hard-hat-detection-for-enforcing-workplace-safety\/\" bis_size='{\"x\":52,\"y\":2804,\"w\":120,\"h\":17,\"abs_x\":610,\"abs_y\":3105}' data-mce-href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/03\/03\/deploy-hard-hat-detection-for-enforcing-workplace-safety\/\" target=\"_blank\"\u003eالكشف عن خوذة الأمان\u003c\/a\u003e وبناء نظام كشف مخصص لمعدات الحماية الشخصية\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\" bis_size='{\"x\":52,\"y\":2839,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3140}'\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":52,\"y\":2839,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3140}'\u003e\u003ca href=\"https:\/\/alwaysai.co\/blog\/using-pose-estimation-on-the-jetson-nano-with-alwaysai\" bis_size='{\"x\":52,\"y\":2840,\"w\":193,\"h\":17,\"abs_x\":610,\"abs_y\":3141}' data-mce-href=\"https:\/\/alwaysai.co\/blog\/using-pose-estimation-on-the-jetson-nano-with-alwaysai\" target=\"_blank\"\u003eتقدير الوضعية مع alwaysAI\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\" bis_size='{\"x\":52,\"y\":2875,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3176}'\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":52,\"y\":2875,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3176}'\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/gtc\/2020\/video\/s22675-vid\" bis_size='{\"x\":52,\"y\":2876,\"w\":355,\"h\":17,\"abs_x\":610,\"abs_y\":3177}' data-mce-href=\"https:\/\/developer.nvidia.com\/gtc\/2020\/video\/s22675-vid\" target=\"_blank\"\u003eالكشف المرئي عن الحالات الشاذة باستخدام NVIDIA Deepstream IoT\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\" bis_size='{\"x\":52,\"y\":2910,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3211}'\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":52,\"y\":2910,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3211}'\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/06\/08\/retail-store-items-detection-using-yolov5-roboflow-and-node-red\/\" bis_size='{\"x\":52,\"y\":2911,\"w\":176,\"h\":17,\"abs_x\":610,\"abs_y\":3212}' data-mce-href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/06\/08\/retail-store-items-detection-using-yolov5-roboflow-and-node-red\/\" target=\"_blank\"\u003eالكشف عن عناصر متجر البيع بالتجزئة\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\" bis_size='{\"x\":52,\"y\":2946,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3247}'\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":52,\"y\":2946,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3247}'\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" bis_size='{\"x\":52,\"y\":2947,\"w\":114,\"h\":17,\"abs_x\":610,\"abs_y\":3248}' data-mce-href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eالكشف عن حرائق الغابات\u003c\/a\u003e\u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli dir=\"ltr\" bis_size='{\"x\":52,\"y\":2981,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3282}'\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":52,\"y\":2981,\"w\":510,\"h\":19,\"abs_x\":610,\"abs_y\":3282}'\u003e\u003ca href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" bis_size='{\"x\":52,\"y\":2982,\"w\":108,\"h\":17,\"abs_x\":610,\"abs_y\":3283}' data-mce-href=\"https:\/\/github.com\/Seeed-Studio\/node-red-contrib-ml\" target=\"_blank\"\u003eالكشف عن الحيوانات\u003c\/a\u003e \u003c\/p\u003e\n\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003cp dir=\"ltr\" bis_size='{\"x\":12,\"y\":3017,\"w\":550,\"h\":58,\"abs_x\":570,\"abs_y\":3318}'\u003eابحث في صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/community\/resources\" bis_size='{\"x\":83,\"y\":3018,\"w\":192,\"h\":17,\"abs_x\":641,\"abs_y\":3319}' data-mce-href=\"https:\/\/developer.nvidia.com\/community\/resources\" target=\"_blank\"\u003eموارد مجتمع Jetson\u003c\/a\u003e عن الأدوات والبرامج التعليمية التي أنشأها المجتمع لتعزيز تجربة التطوير الخاصة بك، واطلع على صفحة \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/community\/jetson-projects\" bis_size='{\"x\":12,\"y\":3038,\"w\":505,\"h\":36,\"abs_x\":570,\"abs_y\":3339}' data-mce-href=\"https:\/\/developer.nvidia.com\/embedded\/community\/jetson-projects\" target=\"_blank\"\u003eمشاريع المجتمع\u003c\/a\u003e لإلهام مشروعك التالي! \u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":3092,\"w\":550,\"h\":39,\"abs_x\":570,\"abs_y\":3393}'\u003eيرجى أيضًا الاطلاع على \u003ca href=\"https:\/\/wiki.seeedstudio.com\/reComputer_Jetson_Series_Started_Guide\/\" bis_size='{\"x\":155,\"y\":3093,\"w\":116,\"h\":17,\"abs_x\":713,\"abs_y\":3394}' data-mce-href=\"https:\/\/wiki.seeedstudio.com\/reComputer_Jetson_Series_Started_Guide\/\" target=\"_blank\"\u003e\u003cstrong bis_size='{\"x\":155,\"y\":3093,\"w\":116,\"h\":17,\"abs_x\":713,\"abs_y\":3394}'\u003eدليل Seeed wiki\u003c\/strong\u003e\u003c\/a\u003e الذي يتضمن كيفية البدء مع Jetson Nano وأيضًا بناء مشاريع مختلفة. \u003c\/div\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":3131,\"w\":550,\"h\":19,\"abs_x\":570,\"abs_y\":3432}'\u003e\u003cbr bis_size='{\"x\":12,\"y\":3132,\"w\":0,\"h\":17,\"abs_x\":570,\"abs_y\":3433}'\u003e\u003c\/div\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":3151,\"w\":550,\"h\":1220,\"abs_x\":570,\"abs_y\":3452}'\u003e\u003cimg src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/102991695_2.jpg\" data-src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/102991695_2.jpg\" height=\"1200\" width=\"1200\" class=\"lazy\" bis_size='{\"x\":12,\"y\":3151,\"w\":1200,\"h\":1200,\"abs_x\":570,\"abs_y\":3452}' data-mce-src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/102991695_2.jpg\"\u003e\u003c\/div\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":4371,\"w\":550,\"h\":19,\"abs_x\":570,\"abs_y\":4672}'\u003e\u003cbr bis_size='{\"x\":12,\"y\":4372,\"w\":0,\"h\":17,\"abs_x\":570,\"abs_y\":4673}'\u003e\u003c\/div\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":4391,\"w\":550,\"h\":898,\"abs_x\":570,\"abs_y\":4692}'\u003e\n\n\u003cdiv bis_size='{\"x\":12,\"y\":4391,\"w\":550,\"h\":898,\"abs_x\":570,\"abs_y\":4692}'\u003e\n\n\u003cdiv class=\"document\" bis_size='{\"x\":12,\"y\":4391,\"w\":550,\"h\":898,\"abs_x\":570,\"abs_y\":4692}'\u003e\n\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" bis_size='{\"x\":12,\"y\":4391,\"w\":550,\"h\":22,\"abs_x\":570,\"abs_y\":4692}'\u003eمقارنة مع لوحات حامل مجموعة تطوير NVIDIA Xavier NX\u003c\/h3\u003e\n\n\u003cp bis_size='{\"x\":12,\"y\":4424,\"w\":550,\"h\":864,\"abs_x\":570,\"abs_y\":4725}'\u003e\u003cimg src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/J202carrierboard.png\" data-src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/J202carrierboard.png\" height=\"860\" width=\"860\" class=\"lazy\" bis_size='{\"x\":12,\"y\":4424,\"w\":860,\"h\":860,\"abs_x\":570,\"abs_y\":4725}' data-mce-src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer\/J202carrierboard.png\"\u003e\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch3 bis_size='{\"x\":12,\"y\":5305,\"w\":550,\"h\":22,\"abs_x\":570,\"abs_y\":5606}'\u003e نظرة عامة على الأجهزة\u003c\/h3\u003e\n\n\u003cp bis_size='{\"x\":12,\"y\":5338,\"w\":550,\"h\":904,\"abs_x\":570,\"abs_y\":5639}'\u003e\u003cimg class=\"lazy\" width=\"900\" height=\"900\" data-src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202 FRONT.png\" src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20FRONT.png\" bis_size='{\"x\":12,\"y\":5338,\"w\":900,\"h\":900,\"abs_x\":570,\"abs_y\":5639}' data-mce-src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20FRONT.png\"\u003e\u003c\/p\u003e\n\n\u003cp bis_size='{\"x\":12,\"y\":6259,\"w\":550,\"h\":864,\"abs_x\":570,\"abs_y\":6560}'\u003e\u003cimg class=\"lazy\" width=\"860\" height=\"860\" data-src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202 BACK.png\" src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20BACK.png\" bis_size='{\"x\":12,\"y\":6259,\"w\":860,\"h\":860,\"abs_x\":570,\"abs_y\":6560}' data-mce-src=\"https:\/\/files.seeedstudio.com\/products\/102991695\/J202%20BACK.png\"\u003e\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e","brand":"ThinkRobotics","offers":[{"title":"Passive \/ Not Included","offer_id":40067918168150,"sku":"SBC1026-0","price":28749.99,"currency_code":"INR","in_stock":false},{"title":"Passive \/ 12V 6A","offer_id":40067937108054,"sku":"SBC1026-1","price":29999.99,"currency_code":"INR","in_stock":false},{"title":"Active \/ Not Included","offer_id":40067918200918,"sku":"SBC1026-2","price":29749.99,"currency_code":"INR","in_stock":false},{"title":"Active \/ 12V 6A","offer_id":40067937239126,"sku":"SBC1026-3","price":30999.99,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/products\/SBC1026-2.png?v=1663834556"},{"product_id":"nvidia-jetson-agx-xavier-embedded-system-kit","title":"مجموعة نظام NVIDIA Jetson AGX Xavier المدمج من ThinkRobotics","description":"\u003cmeta charset=\"UTF-8\"\u003e\n\u003ch2 style=\"text-align: center;\" data-mce-fragment=\"1\" data-mce-style=\"text-align: center;\"\u003e\u003cstrong\u003eطقم تطوير ThinkRobotics™️ Jetson AGX Xavier\u003c\/strong\u003e\u003c\/h2\u003e\n\u003ch3 style=\"text-align: center;\" data-mce-style=\"text-align: center;\"\u003e\n\n\u003cmeta charset=\"UTF-8\"\u003e \u003cspan\u003eتوفر سلسلة وحدات Jetson AGX Xavier أداء ذكاء اصطناعي يصل إلى 32 عملية في الثانية (TOPS) مع مجموعة غنية من أدوات سير عمل الذكاء الاصطناعي من NVIDIA، مما يتيح للمطورين تدريب ونشر الشبكات العصبية بسرعة.\u003c\/span\u003e\n\n\u003c\/h3\u003e\n\u003cp style=\"text-align: left;\" data-mce-fragment=\"1\" data-mce-style=\"text-align: left;\"\u003e\u003cstrong\u003e\u003c\/strong\u003eتم تجميع هذا النظام المدمج القوي بواسطة ThinkRobotics باستخدام لوحة حاملة (Carrier Board) من الدرجة الصناعية من Forecr.io، ومبدد حراري، ومزود طاقة من Meanwell. هذا الجهاز مخصص لتطبيقات الذكاء الاصطناعي الطرفية بمستوى الحواسيب الفائقة التي تتطلب كاميرات متعددة من نوع MIPI CSI-2. نقوم بتثبيت Jetpack على كل جهاز قبل الشحن؛ بالنسبة للتثبيتات المخصصة، أو الإقلاع عبر NVMe SSD، يرجى الاتصال بنا بعد إتمام الطلب.\u003c\/p\u003e\n\u003ch3 style=\"text-align: left;\" data-mce-fragment=\"1\" data-mce-style=\"text-align: left;\"\u003eتشمل الحزمة:\u003c\/h3\u003e\n\u003cul\u003e\n\n\u003cli\u003eنظام مدمج مُجمع مع:\u003c\/li\u003e\n\n\u003cul\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-agx-xavier-module\" target=\"_blank\"\u003eوحدة AGX Xavier SOM (بسعة 32 جيجابايت أو 64 جيجابايت)\u003c\/a\u003e أو \u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia-jetson-agx-xavier-industrial?_pos=2\u0026amp;_sid=cf83a9438\u0026amp;_ss=r\" target=\"_blank\"\u003eوحدة AGX Industrial SOM\u003c\/a\u003e\n\n\u003c\/li\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/thinkrobotics.in\/products\/forecr-jetson-xavier-agx-carrier-board\" target=\"_blank\"\u003eلوحة حاملة Forecr DSBOARD-XV2\u003c\/a\u003e\n\n\u003c\/li\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia%C2%AE-jetson-agx-xavier%E2%84%A2-passive-heat-sink\" target=\"_blank\"\u003eمبدد حراري سلبي (Passive)\u003c\/a\u003e أو \u003ca href=\"https:\/\/thinkrobotics.in\/products\/nvidia%C2%AE-jetson-agx-xavier%E2%84%A2-active-heat-sink\" target=\"_blank\"\u003eمبدد حراري نشط (Active)\u003c\/a\u003e\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003cli\u003eهيكل مطبوع بتقنية ثلاثية الأبعاد من ألياف الكربون ABS\u003c\/li\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/thinkrobotics.in\/products\/meanwell-gs120a24-p1m-ac-dc-industrial-desktop-adaptor-24v-5a\" target=\"_blank\"\u003eمزود طاقة Meanwell بقدرة 120 واط (24 فولت\/5 أمبير)\u003c\/a\u003e (معدل مع موصل)\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003cblockquote\u003e\n\n\u003cp style=\"text-align: left;\" data-mce-fragment=\"1\" data-mce-style=\"text-align: left;\"\u003eقد تكون هناك فترة تجهيز تصل إلى أسبوعين على بعض الأنواع\u003cbr\u003e\u003c\/p\u003e\n\n\n\u003c\/blockquote\u003e\n\u003ch3 data-mce-fragment=\"1\"\u003eمراجع مهمة:\u003c\/h3\u003e\n\u003cul\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/hs.forecr.io\/hubfs\/DATASHEETS\/dsboard-xv2-datasheet-1.0.pdf\" target=\"_blank\"\u003eورقة البيانات\u003c\/a\u003e\u003cbr\u003e\n\n\u003c\/li\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/www.forecr.io\/blogs\/installation\/jetpack-4-6-installation-for-dsboard-xv2\" target=\"_blank\"\u003eتعليمات\u003c\/a\u003e التثبيت\n\n\u003c\/li\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/www.forecr.io\/blogs\/getting-started\/dsboard-xv2-getting-started\" target=\"_blank\"\u003eدليل\u003c\/a\u003e البدء السريع\n\n\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003cdiv style=\"text-align: center;\" data-mce-style=\"text-align: center;\"\u003e\u003cimg style=\"float: none;\" alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/dsboard-xv2-dark-bg-with-features.webp?v=1651022572\" data-mce-style=\"float: none;\"\u003e\u003c\/div\u003e\n\u003cdiv data-id=\"1618851835946\" data-ver=\"1\" data-icon=\"gpicon-heading\" class=\"element-wrap\" id=\"e-1618851835946\" data-key=\"heading\" data-label=\"Heading\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-center gf-elm--lg gf-elm--md gf-elm--sm gf-elm--xs gf-elm-justify-sm gf-elm-justify-xs gf-elm-left-md gf-elm-justify-lg\"\u003e\n\n\u003ch2\u003e\u003cb\u003eأداء فائق في عمليات نشر الذكاء الاصطناعي\u003c\/b\u003e\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\u003cdiv data-id=\"1618851817638\" data-ver=\"1\" data-icon=\"gpicon-textblock\" class=\"element-wrap\" id=\"e-1618851817638\" data-key=\"text-block\" data-label=\"Text Block\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-left gf-elm-justify-md gf-elm-justify-sm gf-elm-justify-xs gf-elm-justify-lg\"\u003e\n\n\u003cp\u003eDSBOARD-XV2 هي لوحة حاملة صناعية عالية الأداء لمعالج NVIDIA® Jetson™ AGX Xavier™. حجمها المثالي وأداؤها الذي يضاهي الحواسيب الفائقة بـ 32 عملية في الثانية (TOPs) يتيح مجموعة واسعة من التطبيقات، بدءاً من خوارزميات التعلم العميق وحتى الآلات ذاتية التحكم. يمكن لـ Jetson™ AGX Xavier™ ترميز ما يصل إلى 8 تدفقات فيديو بدقة 4K وفك ترميز 12 تدفقاً بدقة 4K.\u003c\/p\u003e\n\n\u003cp\u003eتوفر مكتبة NVIDIA® TensorRT وإطار عمل Deepstream أساساً لأقصى أداء لمعالج NVIDIA® Jetson™ AGX Xavier™. جنباً إلى جنب مع التحسينات المطلوبة في العوامل المدمجة، فإن الحصول على معدلات إطارات بمستوى وحدات معالجة الرسوميات المكتبية (GPU) مع خوارزميات التعلم العميق ليس مفاجئاً. لمزيد من التفاصيل حول أداء معالجات NVIDIA® Jetson™، يمكنك زيارة موقع DeepStream SDK الخاص بـ NVIDIA®.\u003c\/p\u003e\n\n\u003cp\u003e \u003cbr\u003e\u003c\/p\u003e\n\n\u003cdiv data-id=\"1618852408202\" data-ver=\"1\" data-icon=\"gpicon-heading\" class=\"element-wrap\" id=\"e-1618852408202\" data-key=\"heading\" data-label=\"Heading\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-center gf-elm-justify-sm gf-elm-justify-xs gf-elm-left-md gf-elm-justify-lg\"\u003e\n\n\u003ch2\u003e\u003cb\u003eجاهز للاستخدام دائماً\u003c\/b\u003e\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv data-id=\"1618852412098\" data-ver=\"1\" data-icon=\"gpicon-textblock\" class=\"element-wrap\" id=\"e-1618852412098\" data-key=\"text-block\" data-label=\"Text Block\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-left gf-elm-justify-lg gf-elm-justify-md gf-elm-justify-sm gf-elm-justify-xs\"\u003e\n\n\u003cp\u003eتدعم DSBOARD-XV2 كلاً من Jetson™ AGX Xavier™ و Jetson™ AGX Xavier™ Industrial بجميع مميزاتهما. نحن نوفر أحدث إصدار من حزم BSP لـ Jetpack التي تقدمها NVIDIA®. في غضون أسبوعين فقط من إعلان Jetpack الجديد، نقوم بنشر دروس إضافية تتعلق بالاتصال ونظام التشغيل على صفحات مدونتنا.\u003c\/p\u003e\n\n\u003cp\u003eبصفتنا Forecr، نقدم أيضاً حلولاً لمشاكل التكامل الميكانيكي لعملائنا على مستوى اللوحة الحاملة. لضمان عمل وحدات Jetson™ بكفاءة حتى تحت أقصى الأحمال، أنشأنا خيار لوحة نقل حراري. عند طلب DSBOARD-XV2 مع خيار وحدة، سيتم تضمين وحدة نقل الحرارة المناسبة ومجموعة البراغي في الحزمة. نحن نقوم بدمج الوحدة والأجزاء الميكانيكية باللوحة الحاملة، وتثبيت أحدث برامج Jetpack، وحزمة BSP الخاصة بنا لتسليم نظام جاهز للاستخدام بين يديك.\u003c\/p\u003e\n\n\u003cp\u003e \u003cbr\u003e\u003c\/p\u003e\n\n\u003cdiv data-id=\"1618851977475\" data-ver=\"1\" data-icon=\"gpicon-heading\" class=\"element-wrap\" id=\"e-1618851977475\" data-key=\"heading\" data-label=\"Heading\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-center gf-elm-justify-sm gf-elm-left-md gf-elm-center-xs gf-elm-left-lg\"\u003e\n\n\u003ch2\u003e\u003cb\u003eخيارات اتصال غنية\u003c\/b\u003e\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv data-id=\"1618851992166\" data-ver=\"1\" data-icon=\"gpicon-textblock\" class=\"element-wrap\" id=\"e-1618851992166\" data-key=\"text-block\" data-label=\"Text Block\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-left gf-elm-justify-lg gf-elm-justify-md gf-elm-justify-sm gf-elm-justify-xs\"\u003e\n\n\u003cp\u003eتأتي DSBOARD-XV2 مع اتصالات داخلية وخارجية يمكن استخدامها في مجموعة متنوعة من التطبيقات الصناعية. بفضل الواجهات عالية السرعة مثل Gigabit Ethernet و USB 3.1، يمكنك الاتصال بأجهزة عالية السرعة ونقل البيانات بسرعة عرض نطاق ترددي تصل إلى 136.5 جيجابايت\/ثانية. كما قمنا بتضمين واجهات اتصال صناعية مثل CAN Bus ومنافذ RS232\/422\/485 القابلة للتهيئة برمجياً.\u003c\/p\u003e\n\n\u003cp\u003eصُممت DSBOARD-XV2 لتستخدم في العديد من الصناعات المختلفة، لذا قمنا بتضمين موصلات على مستوى اللوحة واتصالات كاميرا غنية أيضاً. تدعم DSBOARD-XV2 ما يصل إلى ست توصيلات كاميرا MIPI CSI-2 متوافقة مع توزيع دبابيس Raspberry Pi القياسي. كما تتوفر موصلات إضافية على مستوى اللوحة بإشارات UART و SPI و I2C و PCIe.\u003c\/p\u003e\n\n\u003cp\u003e \u003cbr\u003e\u003c\/p\u003e\n\n\u003cdiv data-id=\"1618852482764\" data-ver=\"1\" data-icon=\"gpicon-heading\" class=\"element-wrap\" id=\"e-1618852482764\" data-key=\"heading\" data-label=\"Heading\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-center gf-elm-left-md gf-elm-left-sm gf-elm-left-xs gf-elm-left-lg\"\u003e\n\n\u003ch2\u003e\u003cb\u003eأقصى سرعة في الاستخدام\u003c\/b\u003e\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv data-id=\"1618852482720\" data-ver=\"1\" data-icon=\"gpicon-textblock\" class=\"element-wrap\" id=\"e-1618852482720\" data-key=\"text-block\" data-label=\"Text Block\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-left gf-elm-justify-lg gf-elm-justify-md gf-elm-justify-sm gf-elm-justify-xs\"\u003e\n\n\u003cp\u003eتحتوي DSBOARD-XV2 على دعم 4x PCI Gen 4 لفتحة M.2 Key-M SSD، وGigabit Ethernet، و2x USB 3.1، وM.2 Key-B مع اتصال USB 3.1. جنباً إلى جنب مع هذه الواجهات، تتوفر واجهات MIPI CSI-2 على مستوى اللوحة وواجهات بطاقة SD كواجهات عالية السرعة.\u003c\/p\u003e\n\n\u003cp\u003eيتم اختبار النطاقات الترددية لواجهات USB 3.1 مع الكاميرات عالية السرعة، وGigabit Ethernet مع برمجيات تدفق الشبكة، ووظيفية وأداء الإطارات في الثانية لواجهات MIPI CSI-2 مع الكاميرات عالية الدقة، وأداء القراءة\/الكتابة لـ NVMe SSD مع محرك NVMe SSD متوافق مع PCIE GEN4، من قبل فريقنا الهندسي قبل الشحن. نحن نتأكد من أن أداء لوحاتنا الحاملة مستقر وبأقصى كفاءة قبل تسليمها لعملائنا.\u003c\/p\u003e\n\n\u003cp\u003e \u003cbr\u003e\u003c\/p\u003e\n\n\u003cdiv data-id=\"1618852741492\" data-ver=\"1\" data-icon=\"gpicon-heading\" class=\"element-wrap\" id=\"e-1618852741492\" data-key=\"heading\" data-label=\"Heading\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-center gf-elm-left-md gf-elm-left-sm gf-elm-left-xs gf-elm-left-lg\"\u003e\n\n\u003ch2\u003e\u003cb\u003eكفاءة الطاقة مع تحمل طويل الأمد\u003c\/b\u003e\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv data-id=\"1618852741427\" data-ver=\"1\" data-icon=\"gpicon-textblock\" class=\"element-wrap\" id=\"e-1618852741427\" data-key=\"text-block\" data-label=\"Text Block\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-left gf-elm-justify-lg gf-elm-justify-md gf-elm-justify-sm gf-elm-justify-xs\"\u003e\n\n\u003cp\u003eتدعم DSBOARD-XV2 نطاق جهد دخل واسع بالإضافة إلى موصل طاقة موثوق. يمكن توصيل أي مصدر طاقة يتراوح بين 18-32 فولت تيار مستمر، وسيعمل على مدار الساعة طوال أيام الأسبوع، لأسابيع وأشهر دون أي مشاكل حتى تحت أقصى أحمال المعالج (CPU) ومعالج الرسوميات (GPU). تتمتع DSBOARD-XV2 بدوائر طاقة قوية ومتانة لنطاق درجات حرارة ممتد بين -40 درجة مئوية إلى 85 درجة مئوية لتكييف اللوحة مع كل بيئة صناعية.\u003c\/p\u003e\n\n\u003cp\u003eمع ذاكرة الوصول العشوائي (RAM) ذات النطاق الترددي العالي واستهلاك الطاقة المنخفض في Jetson™ AGX Xavier، يمكن تشغيل التطبيقات القوية بكفاءة مع استهلاك كمية صغيرة من الطاقة. تدعم DSBOARD-XV2 أيضاً وحدة تخزين داخلية كبيرة مثل 32 جيجابايت eMMC 5.1 Flash و MicroSD.\u003cbr\u003e\u003c\/p\u003e\n\n\u003cp\u003e \u003cbr\u003e\u003c\/p\u003e\n\n\u003cdiv data-id=\"1618853681889\" data-ver=\"1\" data-icon=\"gpicon-heading\" class=\"element-wrap\" id=\"e-1618853681889\" data-key=\"heading\" data-label=\"Heading\"\u003e\n\n\u003cdiv data-exc=\"\" data-gemlang=\"en\" class=\"elm text-edit gf-elm-center gf-elm-center-md gf-elm-center-sm gf-elm-center-xs gf-elm-center-lg\"\u003e\n\n\u003ch2\u003eالمواصفات الفنية للوحة الحاملة\u003c\/h2\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv data-name=\"Right click on the module, then choose Edit Html \/ Liquid option to start writing your custom code.\" data-id=\"1618852931930\" data-ver=\"1.0\" data-icon=\"gpicon-liquid\" class=\"module-wrap\" id=\"m-1618852931930\" data-key=\"liquid\" data-label=\"Liquid\"\u003e\n\n\u003cdiv class=\"module gf_module- gf_module--lg gf_module--md gf_module--sm gf_module--xs\"\u003e\n\n\u003ctable class=\"table table-bordered\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eالوحدات المدعومة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003eNVIDIA Jetson AGX Xavier\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eالذاكرة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003e32 جيجابايت 256-bit LPDDR4x\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eواجهات الرسوميات\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003e1x HDMI 2.0 (أقصى دقة 3840x2160)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eالواجهات\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\n\n\u003cp\u003e1x Gigabit Ethernet \u003c\/p\u003e\n\n\u003cp\u003e3x USB 3.1\u003c\/p\u003e\n\n\u003cp\u003e1x CAN Bus \u003c\/p\u003e\n\n\u003cp\u003e1x RS232\/422\/485\u003c\/p\u003e\n\n\u003cp\u003e2x دخل رقمي \/ 3x خرج رقمي \u003c\/p\u003e\n\n\u003cp\u003e1x USB 2.0 (تصحيح UART) \u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eالاتصالات اللاسلكية\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003eبطاقات M.2 Key-E اختيارية\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eمزود الطاقة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003e18-32 فولت تيار مستمر\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\n\n\u003cstrong\u003eمآخذ التوسع الداخلية \u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003eSockets\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\u003ctd\u003e1x M.2 Key M (PCIe Gen4 x4)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eوحدة التخزين الداخلية\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\n\n\u003cp\u003e32 جيجابايت eMMC 5.1 Flash \u003c\/p\u003e\n\n\u003cp\u003e1x MicroSD Card\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eالظروف المحيطة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003e-40 درجة مئوية … +85 درجة مئوية \u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eعامل الشكل \/ الأبعاد\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003e100 مم × 100 مم \u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cstrong\u003eأنظمة التشغيل\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd\u003eUbuntu Linux 18.04\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e","brand":"Forecr.io","offers":[{"title":"32GB \/ Passive Heatsink \/ 480GB","offer_id":44410631127357,"sku":"SBC1036-1","price":178749.99,"currency_code":"INR","in_stock":false},{"title":"32GB \/ Passive Heatsink \/ 960GB","offer_id":44410632307005,"sku":"SBC1036-2","price":181749.99,"currency_code":"INR","in_stock":false},{"title":"32GB \/ Active Heatsink \/ 480GB","offer_id":44410631160125,"sku":"SBC1036-3","price":184749.99,"currency_code":"INR","in_stock":false},{"title":"32GB \/ Active Heatsink \/ 960GB","offer_id":44410632339773,"sku":"SBC1036-4","price":188749.99,"currency_code":"INR","in_stock":false},{"title":"Industrial 32GB \/ Passive Heatsink \/ 480GB","offer_id":44410648920381,"sku":"SBC1036-9","price":222749.99,"currency_code":"INR","in_stock":false},{"title":"Industrial 32GB \/ Passive Heatsink \/ 960GB","offer_id":44410648953149,"sku":"SBC1036-10","price":226749.99,"currency_code":"INR","in_stock":false},{"title":"Industrial 32GB \/ Active Heatsink \/ 480GB","offer_id":44410648985917,"sku":"SBC1036-11","price":228749.99,"currency_code":"INR","in_stock":false},{"title":"Industrial 32GB \/ Active Heatsink \/ 960GB","offer_id":44410649018685,"sku":"SBC1036-12","price":232749.99,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/products\/AGX-2.png?v=1674371547"},{"product_id":"nvidia-jetson-orin-nano-developer-kit","title":"مجموعة مطوري NVIDIA Jetson Orin Nano Super","description":"\u003ch2 style=\"text-align: center;\"\u003eمجموعة المطورين NVIDIA Jetson Orin™ Nano Super\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cmeta charset=\"UTF-8\"\u003e\u003cspan\u003eتعد مجموعة المطورين NVIDIA Jetson Orin Nano™ Super حاسوباً مدمجاً وقوياً يعيد تعريف الذكاء الاصطناعي التوليدي للأجهزة الطرفية الصغيرة. فهي توفر أداء ذكاء اصطناعي يصل إلى 67 TOPS - أي تحسن بمقدار 1.7 ضعف عن الإصدار السابق - لتشغيل أكثر نماذج الذكاء الاصطناعي التوليدي شيوعاً بسلاسة، مثل نماذج الرؤية التحويلية (Vision Transformers)، والنماذج اللغوية الكبيرة، ونماذج الرؤية واللغة، والمزيد.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eملاحظة: الحد الأقصى هو أربع وحدات لكل حساب عميل لاستخدامات البحث والتطوير فقط. تُعفى المؤسسات التعليمية من هذا القيد. مزود الطاقة مشمول في المجموعة.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eللحصول على كميات أكبر، تتوفر \u003cspan style=\"text-decoration: underline; color: rgb(43, 0, 255);\"\u003e\u003cem\u003e\u003ca style=\"color: rgb(43, 0, 255); text-decoration: underline;\" rel=\"noopener\" href=\"https:\/\/thinkrobotics.com\/products\/thinkrobotics-edge-ai-device-with-nvidia-jetson-orin%E2%84%A2-nano-made-in-india?utm_source=copyToPasteBoard\u0026amp;utm_medium=product-links\u0026amp;utm_content=web\" target=\"_blank\"\u003e\u003cstrong\u003eمجموعات نشر NVIDIA Jetson Orin™ Nano\u003c\/strong\u003e\u003c\/a\u003e\u003c\/em\u003e\u003c\/span\u003e.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eالميزات\u003c\/h2\u003e\n\u003ctable style=\"width: 99.5588%;\" border=\"0\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eأداء الذكاء الاصطناعي\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e67 TOPS\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eعرض نطاق الذاكرة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e102 جيجابايت\/ثانية\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eتردد المعالج (CPU)\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e1.7 جيجاهرتز\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eوحدة معالجة الرسوميات (GPU)\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003eمعالج رسوميات بـ 1024 نواة بمعمارية NVIDIA Ampere مع 32 نواة تينسور\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eالمعالج (CPU)\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003eمعالج Arm® Cortex®-A78AE v8.2 سداسي النوى 64-بت، ذاكرة مؤقتة L2 سعة 1.5 ميجابايت + L3 سعة 4 ميجابايت\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eالذاكرة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e8 جيجابايت LPDDR5 بـ 128-بت بسرعة 68 جيجابايت\/ثانية\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eالتخزين\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003eفتحة بطاقة SD وذاكرة NVMe خارجية عبر منفذ M.2 Key M\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eالطاقة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e7 واط – 25 واط\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ctable style=\"width: 99.5588%; height: 957.816px;\" border=\"0\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr style=\"height: 56.9205px;\"\u003e\n\n\u003ctd style=\"text-align: center; width: 99.3512%; height: 56.9205px;\" height=\"46\" width=\"935\" colspan=\"3\" class=\"et3\"\u003e\n\n\u003ch3\u003eإعدادات مجموعة المطورين Jetson Orin Nano Super\u003c\/h3\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 122.983px;\"\u003e\n\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 122.983px;\" height=\"123\" width=\"262\" class=\"et5\"\u003e \u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 122.983px;\" width=\"351\" class=\"et6\"\u003e\u003cstrong\u003eمجموعة المطورين NVIDIA Jetson Orin Nano (الأصلية)\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 122.983px;\" width=\"320\" class=\"et6\"\u003e\u003cstrong\u003eمجموعة المطورين NVIDIA Jetson Orin Nano Super\u003c\/strong\u003e\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 273.949px;\"\u003e\n\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 273.949px;\" height=\"274\" width=\"262\" class=\"et6\"\u003e\n\n\u003cbr\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 273.949px;\" width=\"351\" class=\"et5\"\u003e\n\n\u003cbr\u003eمعمارية NVIDIA Ampere\u003cbr\u003e1,024 نواة CUDA\u003cbr\u003e32 نواة تينسور\u003cbr\u003e635 ميجاهرتز\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 273.949px;\" width=\"320\" class=\"et5\"\u003e\n\n\u003cbr\u003eمعمارية NVIDIA Ampere\u003cbr\u003e1,024 نواة CUDA\u003cbr\u003e32 نواة تينسور\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e1,020 ميجاهرتز\u003c\/span\u003e\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 180px;\"\u003e\n\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 180px;\" height=\"180\" width=\"262\" class=\"et6\"\u003e\n\n\u003cbr\u003e\u003cstrong\u003eأداء الذكاء الاصطناعي\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 180px;\" width=\"351\" class=\"et5\"\u003e\n\n\u003cbr\u003e40 TOPS بتقنية INT8 (متفرق)\u003cbr\u003e20 TOPS بتقنية INT8 (كثيف)\u003cbr\u003e10 TFLOPs بتقنية FP16\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 180px;\" width=\"320\" class=\"et5\"\u003e\n\n\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e67 TOPS (متفرق)\u003cbr\u003e33 TOPS (كثيف)\u003cbr\u003e17 TFLOPs بتقنية FP16\u003c\/span\u003e\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 150.966px;\"\u003e\n\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 150.966px;\" height=\"151\" width=\"262\" class=\"et6\"\u003e\n\n\u003cbr\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 150.966px;\" width=\"351\" class=\"et5\"\u003eمعالج Arm Cortex-\u003cbr\u003eA78AE v8.2 64-بت\u003cbr\u003e1.5 جيجاهرتز\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 150.966px;\" width=\"320\" class=\"et5\"\u003eمعالج Arm Cortex-\u003cbr\u003eA78AE v8.2 64-بت\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e1.7 جيجاهرتز\u003c\/span\u003e\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 125px;\"\u003e\n\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 125px;\" height=\"125\" width=\"262\" class=\"et6\"\u003e\n\n\u003cbr\u003e\u003cstrong\u003eالذاكرة\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 125px;\" width=\"351\" class=\"et5\"\u003e8 جيجابايت LPDDR5 بـ 128-بت\u003cbr\u003e68 جيجابايت\/ثانية\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 125px;\" width=\"320\" class=\"et5\"\u003e8 جيجابايت LPDDR5 بـ 128-بت\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e102 جيجابايت\/ثانية\u003c\/span\u003e\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr style=\"height: 47.9972px;\"\u003e\n\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 47.9972px;\" height=\"48\" width=\"262\" class=\"et6\"\u003e\u003cstrong\u003eطاقة الوحدة\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 47.9972px;\" width=\"351\" class=\"et5\"\u003e7 واط | 15 واط\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 47.9972px;\" width=\"320\" class=\"et5\"\u003e7 واط | 15 واط | \u003cstrong\u003e\u003cspan class=\"font1\"\u003e25 واط\u003c\/span\u003e\u003c\/strong\u003e\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e","brand":"NVIDIA","offers":[{"title":"Default Title","offer_id":44900111188285,"sku":"SBC1047","price":54999.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/jetson-orin-nano-super-developer-kit-og.jpg?v=1737536404"},{"product_id":"jetson-agx-xavier-industrial-box-pc-dsbox-xv2","title":"جهاز الكمبيوتر الصناعي Jetson AGX Xavier - DSBOX-XV2","description":"\u003cmeta charset=\"utf-8\"\u003e\n\u003ch2 style=\"text-align: center;\"\u003eجهاز كمبيوتر صناعي صندوقي لـ \u003cspan\u003eNVIDIA Jetson AGX Xavier™ \u003c\/span\u003e\n\n\u003c\/h2\u003e\n\u003ch3 style=\"text-align: center;\"\u003eلتطبيقات الذكاء الاصطناعي المتطورة بمستوى الحواسيب الفائقة\u003c\/h3\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2 style=\"font-weight: 500;\"\u003e\u003cb\u003e\u003cstrong\u003eأداء فائق في نشر الذكاء الاصطناعي\u003c\/strong\u003e\u003c\/b\u003e\u003c\/h2\u003e\n\u003cp\u003eDSBOX-XV2 هو جهاز حوسبة طرفية قوي مصمم للتطبيقات الصناعية التي تتطلب قدرة معالجة عالية وموثوقية. يعمل الجهاز بواسطة وحدة NVIDIA Jetson AGX Xavier™، التي تتميز بمعالج رسومات NVIDIA Volta™ مع 512 نواة CUDA ووحدة معالجة مركزية ARM64 ثمانية النواة. يوفر هذا لـ DSBOX-XV2 قدرة المعالجة المطلوبة للتطبيقات الصناعية المعقدة مثل التعلم الآلي، والرؤية الحاسوبية، والذكاء الاصطناعي.\u003c\/p\u003e\n\u003cp\u003eDSBOX-XV2 عبارة عن لوحة حاملة صناعية عالية الأداء لمعالج NVIDIA Jetson AGX Xavier™. إن حجمه المثالي وأداءه بمستوى الحواسيب الفائقة الذي يصل إلى 32 عملية في الثانية (TOPs) يتيح مجموعة واسعة من التطبيقات، بدءاً من خوارزميات التعلم العميق وصولاً إلى الآلات ذاتية التحكم. يمكن لـ Jetson AGX Xavier™ تشفير ما يصل إلى 8 تدفقات بدقة 4K وفك تشفير 12 تدفقاً بدقة 4K.\u003c\/p\u003e\n\u003ch2 style=\"font-weight: 500;\"\u003e\u003cb\u003e\u003cstrong\u003e \u003c\/strong\u003e\u003c\/b\u003e\u003c\/h2\u003e\n\u003ch2 style=\"font-weight: 500;\"\u003e\n\n\u003cb\u003e\u003cstrong\u003eاستخدام بأقصى سرعة\u003c\/strong\u003e\u003c\/b\u003e\u003cbr\u003e\n\n\u003c\/h2\u003e\n\u003cp\u003eيتميز الجهاز بمنفذ Gigabit Ethernet للشبكات السلكية عالية السرعة، بالإضافة إلى منفذي USB3.1 من النوع A لنقل البيانات بسرعة. علاوة على ذلك، يأتي الجهاز مزوداً بواجهات CAN Bus و RS232\/422\/485، والتي يمكن تهيئتها برمجياً لتناسب التطبيقات المختلفة. لمزيد من المرونة، يتضمن DSBOX-XV2 أيضاً مدخلين رقميين وثلاثة مخارج رقمية، مما يسهل دمجه مع الأنظمة الصناعية الأخرى. كما يتميز بمنافذ من النوع C لأغراض التصحيح والاستعادة، بالإضافة إلى منفذ HDMI 2.0 يدعم دقة تصل إلى 3840x2160، مما يوفر مخرجات رسومية عالية الجودة.\u003c\/p\u003e\n\u003cp\u003eعلاوة على ذلك، يتضمن الجهاز مقبس M.2 Key-E وفتحة MicroSD للتوسعة، مما يتيح للمستخدمين إضافة خيارات اتصال إضافية حسب الحاجة. ومع وجود فتحة M.2 Key-M SSD، يمكن تهيئة DSBOX-XV2 باستخدام وحدة تخزين ذات حالة صلبة عالية السرعة للوصول إلى البيانات ونقلها بسرعة. يوفر DSBOX-XV2 مجموعة شاملة من خيارات الاتصال والواجهات، مما يجعله جهاز حوسبة طرفية صناعياً متعدد الاستخدامات ومرناً. إن نطاقه الواسع من الواجهات، والمدخلات والمخرجات الرقمية، ودعمه لخيارات التوسعة، يجعله الخيار الأمثل لمجموعة واسعة من التطبيقات الصناعية.\u003c\/p\u003e\n\u003ch2 style=\"font-weight: 500;\"\u003e\u003cb\u003e\u003cstrong\u003e \u003c\/strong\u003e\u003c\/b\u003e\u003c\/h2\u003e\n\u003ch2 style=\"font-weight: 500;\"\u003e\u003cb\u003e\u003cstrong\u003eجاهز للاستخدام دائماً\u003c\/strong\u003e\u003c\/b\u003e\u003c\/h2\u003e\n\u003cp\u003eتم تصميم DSBOX-XV2 للعمل بشكل موثوق في مجموعة واسعة من الظروف المحيطة، مع نطاق درجة حرارة من -25 درجة مئوية إلى +85 درجة مئوية. وهذا يجعله خياراً مثالياً للاستخدام في البيئات الصناعية حيث يمكن أن تتفاوت درجات الحرارة بشكل كبير. سواء كنت تعمل في حرارة شديدة أو برودة قاسية، فقد صُمم DSBOX-XV2 للتعامل مع كل ذلك، مما يوفر أداء حوسبة قوياً وموثوقاً بغض النظر عن البيئة.\u003c\/p\u003e\n\u003cp\u003eبالإضافة إلى تصميمه القوي ونطاق درجة حرارة التشغيل الواسع، يتميز DSBOX-XV2 أيضاً بشكل مضغوط يجعله سهل التركيب والاستخدام في مجموعة متنوعة من الإعدادات الصناعية. بأبعاد 160 مم × 110 مم × 95 مم ووزن 1340 جراماً، يعد الجهاز خفيف الوزن وسهل التعامل. كما يعني حجمه الصغير أنه يمكن دمجه بسهولة في الأنظمة الصناعية الحالية، مما يوفر أداء حوسبة قوياً دون أن يشغل مساحة كبيرة.\u003c\/p\u003e\n\u003ch2 style=\"font-weight: 500;\"\u003e\u003cb\u003e\u003cstrong\u003e \u003c\/strong\u003e\u003c\/b\u003e\u003c\/h2\u003e\n\u003ch2 style=\"font-weight: 500;\"\u003e\u003cb\u003e\u003cstrong\u003eحوسبة طرفية متعددة الاستخدامات\u003c\/strong\u003e\u003c\/b\u003e\u003c\/h2\u003e\n\u003cp\u003eتم تصميم DSBOX-XV2 للعمل مع مجموعة واسعة من مصادر الطاقة، مع نطاق جهد دخل من 18-30 فولت تيار مستمر. وهذا يعني أنه يمكن أن يعمل في مجموعة متنوعة من البيئات الصناعية، حتى في الحالات التي قد تكون فيها الطاقة غير مستقرة أو متذبذبة. بفضل تصميمه القوي ودعمه لمجموعة واسعة من دخلات الطاقة، يعد DSBOX-XV2 جهاز حوسبة موثوقاً وقوياً ومناسباً جداً للاستخدام في البيئات الصناعية القاسية.\u003c\/p\u003e\n\u003cp\u003eبشكل عام، يعد DSBOX-XV2 جهاز حوسبة طرفية قوياً ومتعدد الاستخدامات يوفر مجموعة واسعة من خيارات الاتصال والطاقة. مع دعم الاتصال اللاسلكي ونطاق جهد دخل واسع، فهو حل موثوق ومرن لمجموعة واسعة من التطبيقات الصناعية. سواء كنت تتطلع إلى تحسين عمليات التصنيع الخاصة بك، أو تعزيز سلامة النقل، أو تبسيط إدارة الطاقة، فإن DSBOX-XV2 هو الحل الأمثل لاحتياجات الحوسبة الصناعية الخاصة بك.\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2\u003eالموارد\u003c\/h2\u003e\n\u003cul\u003e\n\n\u003cli\u003e\u003ca href=\"https:\/\/hs.forecr.io\/hubfs\/DATASHEETS\/dsbox-xv2-datasheet-v1.0.pdf\" target=\"_blank\"\u003eورقة البيانات\u003c\/a\u003e\u003c\/li\u003e\n\n\u003cli\u003e\u003ca href=\"https:\/\/github.com\/mistelektronik\/forecr_3d_models\/tree\/master\/DSBOX-XV2\" target=\"_blank\"\u003eنموذج ثلاثي الأبعاد\u003c\/a\u003e\u003c\/li\u003e\n\n\u003cli\u003e\u003ca href=\"https:\/\/www.forecr.io\/blogs\/installation\/jetpack-5-1-installation-for-dsboard-xv2\" target=\"_blank\"\u003eالتثبيت\u003c\/a\u003e\u003c\/li\u003e\n\n\u003cli\u003e\n\n\u003ca href=\"https:\/\/www.forecr.io\/products\/jetson-agx-xavier-industrial-box-pc-dsbox-xv2\" target=\"_blank\"\u003eدليل البدء السريع\u003c\/a\u003e \u003c\/li\u003e\n\n\u003cli\u003e\u003ca href=\"https:\/\/www.forecr.io\/products\/jetson-agx-xavier-industrial-box-pc-dsbox-xv2#r-1619367341383\" target=\"_blank\"\u003eالمواصفات الفنية\u003c\/a\u003e\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\u003ch2\u003e \u003c\/h2\u003e\n\u003ch2\u003eالمواصفات الفنية\u003c\/h2\u003e\n\u003ctable style=\"width: 70%; margin: auto;\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eالوحدات المدعومة\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\n\n\u003cp\u003eNVIDIA Jetson AGX Xavier 32GB\u003c\/p\u003e\n\n\u003cp\u003eNVIDIA Jetson AGX Xavier 64GB\u003c\/p\u003e\n\n\u003cp\u003eNVIDIA Jetson AGX Xavier Industrial 32GB\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eالذاكرة\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e32 \/ 64 جيجابايت 256-بت LPDDR4x\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eواجهات الرسومات\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e1x HDMI 2.0 (دقة قصوى 3840x2160)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eالواجهات\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\n\n\u003cp\u003e1x Gigabit Ethernet \u003c\/p\u003e\n\n\u003cp\u003e2x USB 3.1 Type-A\u003c\/p\u003e\n\n\u003cp\u003e1x CAN Bus \u003c\/p\u003e\n\n\u003cp\u003e1x RS232\/422\/485 (قابل للتهيئة برمجياً)\u003c\/p\u003e\n\n\u003cp\u003e2x Type-C (تصحيح\/استعادة)\u003c\/p\u003e\n\n\u003cp\u003e2x دخل رقمي، 3x مخرج رقمي \u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eالاتصال اللاسلكي\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003eاتصال WiFi\/Bluetooth عبر مقابس التوسعة\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eمصدر الطاقة\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e18-30 فولت تيار مستمر\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eمقابس التوسعة\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e1x M.2 Key-E, 1x MicroSD\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eتخزين البيانات\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\n\n\u003cp\u003e32 \/ 64 جيجابايت eMMC 5.1 Flash \u003c\/p\u003e\n\n\u003cp\u003e1x M.2 Key-M SSD Slot\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eالظروف المحيطة\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e-25 درجة مئوية … +85 درجة مئوية \u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eعامل الشكل \/ الأبعاد\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e160 مم x 110 X 95 مم، 1340 جم \u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eأنظمة التشغيل\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003eUbuntu Linux 18.04 \/ 20.04\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd\u003e\u003cb\u003e\u003cstrong\u003eدعم JetPack\u003c\/strong\u003e\u003c\/b\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\n\n\u003cp\u003eJetPack 4.x (4.4.1 \/ 4.5 \/ 4.5.1 \/ 4.6 \/ 4.6.1 \/ 4.6.2 \/ 4.6.3)\u003c\/p\u003e\n\n\u003cp\u003eJetPack 5.x (5.0.2 \/ 5.1)\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e","brand":"Forecr.io","offers":[{"title":"32GB \/ None","offer_id":45117747167549,"sku":"SBC1050-32","price":186999.99,"currency_code":"INR","in_stock":false},{"title":"32GB \/ Power Block (90W)","offer_id":45117745299773,"sku":"SBC1050-32+ELC5075","price":189999.99,"currency_code":"INR","in_stock":false},{"title":"32GB \/ 250GB NVME SSD","offer_id":45117745332541,"sku":"SBC1050-32+SBC2105","price":191899.99,"currency_code":"INR","in_stock":false},{"title":"32GB \/ Power Block (90W) + 250GB NVME SSD","offer_id":45117745365309,"sku":"SBC1050-32+SBC2105+ELC5075","price":196499.99,"currency_code":"INR","in_stock":false},{"title":"32GB Industrial \/ None","offer_id":45117747233085,"sku":"SBC1050-INSTRL","price":229999.99,"currency_code":"INR","in_stock":false},{"title":"32GB Industrial \/ Power Block (90W)","offer_id":45117745496381,"sku":"SBC1050-INSTRL+ELC5075","price":234999.99,"currency_code":"INR","in_stock":false},{"title":"32GB Industrial \/ 250GB NVME SSD","offer_id":45117745529149,"sku":"SBC1050-INSTRL+SBC2105","price":235499.99,"currency_code":"INR","in_stock":false},{"title":"32GB Industrial \/ Power Block (90W) + 250GB NVME SSD","offer_id":45117745561917,"sku":"SBC1050-INSTRL+ELC5075+SBC2105","price":240499.99,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/dsbox-xv2-1.jpg?v=1683103003"},{"product_id":"thinkrobotics-jetson-nano-dev-kit-sub","title":"ThinkRobotics Jetson Nano Dev Kit (SUB)","description":"\u003ch1 style=\"text-align: center;\"\u003eJetson Nano Development \/ Expansion Kit\u003c\/h1\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\n\u003cspan style=\"color: rgb(194, 0, 0);\"\u003eAlternative solution of B01 kit\u003c\/span\u003e\u003cspan\u003e \u003c\/span\u003e\n\u003c\/h3\u003e\n\u003cdiv style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-1.jpg\" alt=\"\" style=\"margin-bottom: 16px; float: none;\"\u003e\u003c\/div\u003e\n\u003cp style=\"text-align: center;\"\u003eBased on AI computers Jetson Nano, providing\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003ealmost the same\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eperipheral interfaces, size and thickness as the Jetson Nano Developer Kit (B01), more convenient for upgrading the core module. By utilizing the power of core module, it is qualified for fields like image classification, object detection, segmentation, speech processing etc. and can be used in sorts of AI projects.\u003c\/p\u003e\n\u003ch2 class=\"richTitle\" style=\"text-align: center;\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"richTitle\" style=\"text-align: center;\"\u003eComparison with B01\u003c\/h2\u003e\n\u003ch4 class=\"richDesc\" style=\"text-align: center;\"\u003ecompatible with expansion modules and cases of the Jetson Nano Developer Kit (B01)\u003c\/h4\u003e\n\u003ctable style=\"width: 90%; margin: auto; height: 1957.64px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 447.188px;\"\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 447.188px; width: 50.65%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-7-1.jpg\"\u003e\n\u003cp\u003e\u003cstrong\u003eJetson Nano Developer Kit (B01)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 447.188px; width: 49.1165%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-7-2.jpg\"\u003e\n\u003cp\u003e\u003cstrong\u003eJETSON-NANO-DEV-KIT\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 63.6094px;\"\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 63.6094px; width: 99.7664%;\" colspan=\"2\"\u003e\n\u003ch3 class=\"richTitle\"\u003eComparing the Storage Solution\u003c\/h3\u003e\n\u003ch4 class=\"richDesc\"\u003e\u003cspan style=\"color: rgb(194, 0, 1);\"\u003edefault storage\u003c\/span\u003e\u003c\/h4\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 479.562px;\"\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 479.562px; width: 50.65%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-5-1.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eJetson Nano Developer Kit (B01)\u003c\/strong\u003e\u003cbr\u003eThe Nano module included in the B01 kit has no storage onboard, external TF card is required to be used as the system startup disk\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 479.562px; width: 49.1165%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-5-2.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eJETSON-NANO-DEV-KIT\u003c\/strong\u003e\u003cbr\u003eIncludes a Nano module with onboard 16GB eMMC, more stable reading\/writing, no extra TF card required for startup disk, providing adequate space for installing system image and development\/study requirement in most cases\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 33.4688px;\"\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 33.4688px; width: 99.7664%;\" colspan=\"2\"\u003e\n\u003ch3 class=\"richDesc\"\u003e\u003cspan style=\"color: rgb(194, 0, 0);\"\u003eExternal Storage Option\u003c\/span\u003e\u003c\/h3\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 440.375px;\"\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 440.375px; width: 50.65%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-6-1.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eJetson Nano Developer Kit (B01)\u003c\/strong\u003e\u003cbr\u003eThe B01 kit requires an external TF card to be used as the system startup disk\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 440.375px; width: 49.1165%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-6-2.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eJETSON-NANO-DEV-KIT\u003c\/strong\u003e\u003cbr\u003eComes with a 64GB TF card, no need to purchase separately, for complicated development projects\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 33.4688px;\"\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; height: 33.4688px; width: 99.7664%;\" colspan=\"2\"\u003e\n\u003ch3 style=\"text-align: center;\" class=\"richDesc\"\u003e\u003cspan style=\"color: rgb(194, 0, 1);\"\u003eExternal TF Card Slot\u003c\/span\u003e\u003c\/h3\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 459.969px;\"\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 459.969px; width: 50.65%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-8-1.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eJetson Nano Developer Kit (B01)\u003c\/strong\u003e\u003cbr\u003eThere is no external TF card slot on the expansion board, it needs to be equipped with a Nano module with a TF card interface\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 0px; vertical-align: top; text-align: center; height: 459.969px; width: 49.1165%;\"\u003e\n\u003cimg class=\"round1234\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-8-2.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eJETSON-NANO-DEV-KIT\u003c\/strong\u003e\u003cbr\u003eSupport TF card. To use this function, you need to modify the device tree file, which is difficult for users who are just getting started. Can be used as memory expansion or startup disk\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cdiv\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003e \u003c\/h2\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003eComparing Specifications\u003c\/h2\u003e\n\u003cbr\u003e\n\u003ctable class=\"tabSty-2 subBlock\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth\u003e \u003c\/th\u003e\n\u003ctd\u003e\u003cstrong\u003eJetson Nano Developer Kit (B01)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003eJETSON-NANO-DEV-KIT\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e128-core Maxwell\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003eQuad-core ARM A57 @ 1.43 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e4 GB 64-bit LPDDR4 25.6 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd\u003eTF card\u003cbr\u003e(NOT included)\u003c\/td\u003e\n\u003ctd\u003e16GB eMMC + 64GB TF card\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eVideo Encoder\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e250 MP\/s\u003cbr\u003e1x 4K @ 30 [HEVC]\u003cbr\u003e2x 1080p @ 60 [HEVC]\u003cbr\u003e4x 1080p @ 30 [HEVC]\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eVideo Decoder\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e500 MP\/s\u003cbr\u003e1x 4K @ 60 [HEVC]\u003cbr\u003e2x 4K @ 30 [HEVC]\u003cbr\u003e4x 1080p @ 60 [HEVC]\u003cbr\u003e8x 1080p @ 30 [HEVC]\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eCamera\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e2x MIPI CSI-2 DPHY lanes\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eConnectivity\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003eGigabit Ethernet, M.2 Key E expansion connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eDisplay\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003eHDMI and DP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eUSB\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e4x USB 3.0, USB 2.0 Micro-B\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cstrong\u003eExtension Interfaces\u003c\/strong\u003e\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003eGPIO, I2C, I2S, SPI, UART\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003eDimensions\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e100 × 80 × 29mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth\u003eOther\u003c\/th\u003e\n\u003ctd colspan=\"2\"\u003e260-pin connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cdiv class=\"pdT\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003cdiv style=\"text-align: center;\"\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003ePlay with Binocular Vision\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\" class=\"richDesc\"\u003eSupports 2-lanes CSI Camera, suitable for binocular vision applications such as parallax algorithm ranging, facial recognition, organism detection, VR video recording...\u003c\/p\u003e\n\u003cimg style=\"margin-bottom: 16px; float: none;\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-3.jpg\"\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"text-align: center;\" class=\"pdT\"\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003e \u003c\/h2\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003eDual 4K outputs\u003c\/h2\u003e\n\u003ch4 style=\"text-align: center;\" class=\"richDesc\"\u003e\u003cspan style=\"color: rgb(194, 0, 0);\"\u003esupports DisplayPort and HDMI high definition ports\u003c\/span\u003e\u003c\/h4\u003e\n\u003cimg style=\"margin-bottom: 16px; float: none;\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-9.jpg\"\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"text-align: center;\"\u003e\n\u003ch2 class=\"richTitle\" style=\"text-align: center;\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"richTitle\" style=\"text-align: center;\"\u003e4x high speed USB3.0\u003c\/h2\u003e\n\u003ch4 class=\"richDesc\" style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(194, 0, 1);\"\u003eUSB3.0 high speed data transmission, allows more USB peripherals\u003c\/span\u003e\u003c\/h4\u003e\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-11.jpg\" style=\"margin-bottom: 16px; float: none;\"\u003e\n\u003c\/div\u003e\n\u003cp\u003e\u003cbr\u003e \u003c\/p\u003e\n\u003cdiv class=\"pdT\" style=\"text-align: center;\"\u003e\n\u003ch2 class=\"richTitle\" style=\"text-align: center;\"\u003eColor-coded 40PIN GPIO header\u003c\/h2\u003e\n\u003ch4 class=\"richDesc\" style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(194, 0, 0);\"\u003ecolor-coded header pins with clear labels, handy for use\u003c\/span\u003e\u003c\/h4\u003e\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-13.jpg\" style=\"margin-bottom: 16px; float: none;\"\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"text-align: center;\"\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003e \u003c\/h2\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003eIntroduction\u003c\/h2\u003e\n\u003cimg style=\"margin-bottom: 16px; float: none;\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-intro.jpg\"\u003e\n\u003col class=\"alignl\"\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003eCore module socket\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003eTF card slot\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003eM.2 Key E connector\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003e1.25mm Fan header\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\n\u003cstrong\u003ePoE pins\u003c\/strong\u003e: PoE module is not included\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003e40PIN GPIO header\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003e2.54mm Fan header\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\n\u003cstrong\u003eMicro USB port:\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor 5V power input or for USB data transmission\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\n\u003cstrong\u003eGigabit Ethernet port:\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003e10\/100\/1000Base-T auto-negotiation, supports PoE if external PoE module is connected\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003e4x USB 3.0 port\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003eHDMI output port\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003eDisplayPort connector\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\n\u003cstrong\u003eDC jack:\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor 5V power input\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003e2x MIPI CSI camera connector\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\u003cstrong\u003eMulti-function 12PIN header\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli style=\"text-align: left;\"\u003e\n\u003cstrong\u003ePWR button:\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003ePower ON\/OFF control (same function as the PWR BTN pin)\u003c\/li\u003e\n\u003c\/ol\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"text-align: center;\"\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003e \u003c\/h2\u003e\n\u003ch2 style=\"text-align: center;\" class=\"richTitle\"\u003eOutline dimensions\u003c\/h2\u003e\n\u003cimg style=\"margin-bottom: 16px; float: none;\" src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-details-size.jpg\"\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"richGridWrap mgnTB\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003ch2 class=\"richTitle\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"richTitle\"\u003eResources\u003c\/h2\u003e\n\u003cp class=\"bgGrey\"\u003e\u003cstrong\u003eWiki:\u003cspan\u003e \u003c\/span\u003e\u003c\/strong\u003e\u003ca href=\"http:\/\/www.waveshare.com\/wiki\/JETSON-NANO-DEV-KIT\" target=\"_blank\"\u003eJETSON-NANO-DEV-KIT\u003c\/a\u003e\u003c\/p\u003e\n\u003ch2 class=\"bgGrey\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"bgGrey\"\u003ePackage Contains:\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eWeight:\u003cspan\u003e \u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e350 grams\u003c\/span\u003e\u003c\/p\u003e\n\u003cdiv class=\"std\"\u003e\n\u003cdiv class=\"sep0px\"\u003e \u003c\/div\u003e\n\u003ch3\u003eJETSON-NANO-DEV-KIT\u003c\/h3\u003e\n\u003col\u003e\n\u003cli\u003eJETSON-IO-BASE-A (carrier board)\u003c\/li\u003e\n\u003cli\u003eJetson Nano module\u003c\/li\u003e\n\u003cli\u003eOfficial heatsink\u003c\/li\u003e\n\u003c\/ol\u003e\n\u003cdiv class=\"imgTextWrap\"\u003e\n\u003cdiv\u003e1\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-IO-BASE-A\/JETSON-IO-BASE-A-4_220.jpg\"\u003e2\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/Jetson-Nano-Module\/Jetson-Nano-Module-2_220.jpg\"\u003e3\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/accessories\/NANO-HEATSINK\/NANO-HEATSINK-1_220.jpg\"\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Waveshare","offers":[{"title":"Default Title","offer_id":49531065467197,"sku":"SBC1108","price":30899.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/jetson-nano-dev-kit-a-1_1_6.jpg?v=1730212078"},{"product_id":"nvidia-jetson-orin-super-nano-deployment-kit-made-in-india","title":"مجموعة تطوير NVIDIA Jetson Orin Super Nano - صُنع في الهند","description":"\u003cdiv class=\"document\"\u003e\n\n\u003cdiv id=\"detail-target-0\" class=\"detail-label-item active\"\u003e\n\n\u003cdiv id=\"product.info.description\" class=\"detail-item-content data item content product data items\"\u003e\n\n\u003cdiv class=\"product attribute description\"\u003e\n\n\u003cdiv class=\"description-content-wrapper\" style=\"text-align: center;\"\u003e\n\n\u003cdiv style=\"text-align: center;\" class=\"pdT\"\u003e\n\n\u003ch2 class=\"richTitle hilitColor\"\u003eNVIDIA Jetson Orin™ Super Nano Deployment Kit - صُنع في الهند\u003c\/h2\u003e\n\n\u003ch4 class=\"hilitBlock2\"\u003e\u003cspan style=\"color: rgb(194, 0, 0);\"\u003eمع لوحة حامل Waveshare\u003c\/span\u003e\u003c\/h4\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-1.jpg\" style=\"margin-bottom: 16px; float: none;\"\u003e\n\u003ch2 class=\"richTitle hilitColor\"\u003e\n\n\u003cspan style=\"color: rgb(194, 0, 1);\"\u003e\u003c\/span\u003e\u003cbr\u003e\n\n\u003c\/h2\u003e\n\n\u003ch2 class=\"richTitle hilitColor\"\u003e\n\n\u003cspan style=\"color: rgb(194, 0, 1);\"\u003eيعتمد على وحدة Jetson Orin Nano\u003c\/span\u003e\u003cbr\u003e\u003cspan style=\"color: rgb(194, 0, 1);\"\u003eمجموعة تطوير الحوسبة المتطورة للذكاء الاصطناعي\u003c\/span\u003e\n\n\u003c\/h2\u003e\n\n\u003ch4 class=\"richDesc\"\u003eهذه ليست مجموعة المطورين الرسمية من N-VIDIA\u003c\/h4\u003e\n\n\u003cp class=\"alignl pdTRBL\"\u003eتتضمن هذه المجموعة وحدة Orin Nano مع خيارات لذاكرة \u003cspan class=\"hilitColor\"\u003e4 جيجابايت\/8 جيجابايت\u003c\/span\u003e، ولا تحتوي على وحدة تخزين مدمجة، وتوفر أداء ذكاء اصطناعي يصل إلى 20 TOPS\/67 TOPS. تأتي مع \u003cspan class=\"hilitColor\"\u003eمحرك أقراص الحالة الصلبة NVMe سعة 256 جيجابايت مثبت مسبقًا\u003c\/span\u003e، وقراءة\/كتابة عالية السرعة، لتلبية احتياجات تطوير مشاريع الذكاء الاصطناعي الكبيرة.\u003c\/p\u003e\n\n\u003cbr\u003eتأتي هذه المجموعة أيضًا مع بطاقة شبكة لاسلكية AW-CB375NF مثبتة مسبقًا تدعم تقنية Bluetooth 5.0 وشبكة Wi-Fi ثنائية النطاق، مع هوائيين إضافيين من نوع PCB، لتوفير اتصال شبكة لاسلكية سريع وموثوق واتصالات بلوتوث.\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: center;\" class=\"pdT\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: center;\" class=\"pdT\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/JETSON-ORIN-NANO-4G-DEV-KIT-details-7.jpg?v=1771656799\" alt=\"\"\u003e\u003c\/div\u003e\n\n\u003cdiv class=\"pdTRBL\"\u003e\n\n\u003cdiv style=\"text-align: center;\"\u003e\n\n\u003cp class=\"alignl pdTRBL\"\u003e \u003c\/p\u003e\n\n\u003ch2 class=\"alignl pdTRBL\"\u003e\u003cstrong class=\"hilitColor\"\u003eJETSON-ORIN-NANO-DEV-KIT\u003c\/strong\u003e\u003c\/h2\u003e\n\n\u003cp class=\"alignl pdTRBL\"\u003eتتضمن وحدة Jetson Orin Nano (خيارات 4 جيجابايت\/8 جيجابايت)، ولوحة القاعدة JETSON-ORIN-IO-BASE، ومروحة تبريد، ومحرك أقراص الحالة الصلبة NVMe سعة 256 جيجابايت\/128 جيجابايت، وبطاقة شبكة لاسلكية ثنائية النطاق AW-CB375NF، وكابل USB، وكابل إيثرنت، ومزود طاقة، إلخ.\u003c\/p\u003e\n\n\n\u003c\/div\u003e\n\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\n\n\u003cdiv\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/JETSON-ORIN-NANO-4G-DEV-KIT_3c62a9a4-1a21-42bb-a689-b6ad4d51b37d.jpg?v=1735817819\"\u003e\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch1 style=\"text-align: center;\"\u003e\u003cstrong class=\"hilitColor\"\u003e \u003c\/strong\u003e\u003c\/h1\u003e\n\n\u003cdiv\u003e\n\n\u003ch2 class=\"richTitle hilitColor\"\u003eمواصفات Jetson Orin Nano\u003c\/h2\u003e\n\n\u003ctable class=\"tabSty-2 subBlock alignc mgnTB\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالوحدة\u003c\/th\u003e\n\n\u003ctd colspan=\"2\"\u003e\u003cstrong class=\"hilitColor\"\u003e4 جيجابايت\u003c\/strong\u003e\u003c\/td\u003e\n\n\u003ctd colspan=\"3\"\u003e\u003cstrong class=\"hilitColor\"\u003e8 جيجابايت\u003c\/strong\u003e\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالإصدار\u003c\/th\u003e\n\n\u003ctd\u003e\u003ca href=\"https:\/\/www.waveshare.com\/jetson-orin-nano.htm?sku=24432\" target=\"_blank\"\u003eوحدة Jetson Orin Nano سعة 4 جيجابايت\u003c\/a\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\u003ca href=\"https:\/\/www.waveshare.com\/jetson-orin-nano-dev-kit.htm?sku=24499\" target=\"_blank\"\u003eمجموعة Waveshare\u003c\/a\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\u003ca href=\"https:\/\/www.waveshare.com\/jetson-orin-nano.htm?sku=24433\" target=\"_blank\"\u003eوحدة Jetson Orin Nano سعة 8 جيجابايت\u003c\/a\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\u003ca href=\"https:\/\/www.waveshare.com\/jetson-orin-nano-dev-kit.htm?sku=24505\" target=\"_blank\"\u003eمجموعة Waveshare\u003c\/a\u003e\u003c\/td\u003e\n\n\u003ctd\u003e\u003ca href=\"https:\/\/www.waveshare.com\/jetson-orin-nano-developer-kit.htm\" target=\"_blank\"\u003eالمجموعة الرسمية\u003c\/a\u003e\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eأداء الذكاء الاصطناعي\u003c\/th\u003e\n\n\u003ctd colspan=\"2\"\u003e20 TOPS\u003c\/td\u003e\n\n\u003ctd colspan=\"3\"\u003e40 TOPS\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eوحدة معالجة الرسومات (GPU)\u003c\/th\u003e\n\n\u003ctd colspan=\"2\"\u003eوحدة معالجة رسومات بمعمارية N-VIDIA Ampere بـ 512 نواة مع 16 نواة Tensor\u003c\/td\u003e\n\n\u003ctd colspan=\"3\"\u003eوحدة معالجة رسومات بمعمارية N-VIDIA Ampere بـ 1024 نواة مع 32 نواة Tensor\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eتردد GPU\u003c\/th\u003e\n\n\u003ctd colspan=\"5\"\u003e625 ميجاهرتز (بحد أقصى)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eوحدة المعالجة المركزية (CPU)\u003c\/th\u003e\n\n\u003ctd colspan=\"5\"\u003eوحدة معالجة مركزية Arm® Cortex®-A78AE v8.2 بـ 64 بت و6 أنوية، ذاكرة تخزين مؤقت L2 سعة 1.5 ميجابايت + L3 سعة 4 ميجابايت\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eتردد CPU\u003c\/th\u003e\n\n\u003ctd colspan=\"5\"\u003e1.5 جيجاهرتز (بحد أقصى)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالذاكرة\u003c\/th\u003e\n\n\u003ctd colspan=\"2\"\u003e4 جيجابايت LPDDR5 بسرعة 64 بت، 32 جيجابايت\/ثانية\u003c\/td\u003e\n\n\u003ctd colspan=\"3\"\u003e8 جيجابايت LPDDR5 بسرعة 128 بت، 68 جيجابايت\/ثانية\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالتخزين\u003c\/th\u003e\n\n\u003ctd\u003eيدعم NVMe خارجي\u003c\/td\u003e\n\n\u003ctd\u003eمحرك أقراص الحالة الصلبة NVMe سعة 128 جيجابايت\u003c\/td\u003e\n\n\u003ctd\u003eيدعم NVMe خارجي\u003c\/td\u003e\n\n\u003ctd\u003eمحرك أقراص الحالة الصلبة NVMe سعة 128 جيجابايت\u003c\/td\u003e\n\n\u003ctd\u003eفتحة بطاقة TF وNVMe خارجي عبر M.2 Key M\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالطاقة\u003c\/th\u003e\n\n\u003ctd colspan=\"2\"\u003e7 وات ~ 10 وات\u003c\/td\u003e\n\n\u003ctd colspan=\"3\"\u003e7 وات ~ 15 وات\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003ePCIE*\u003c\/th\u003e\n\n\u003ctd\u003e1 x4 + 3 x1 (PCIe 3.0, منفذ الجذر ونقطة النهاية)\u003c\/td\u003e\n\n\u003ctd\u003eفتحة M.2 Key M مع x4 PCIe Gen3\/\u003cbr\u003eفتحة M.2 Key M مع x2 PCIe Gen3\/\u003cbr\u003eفتحة M.2 Key E\u003c\/td\u003e\n\n\u003ctd\u003e1 x4 + 3 x1 (PCIe 4.0, منفذ الجذر ونقطة النهاية)\u003c\/td\u003e\n\n\u003ctd colspan=\"2\"\u003eفتحة M.2 Key M مع x4 PCIe Gen3\/\u003cbr\u003eفتحة M.2 Key M مع x2 PCIe Gen3\/\u003cbr\u003eفتحة M.2 Key E\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eUSB*\u003c\/th\u003e\n\n\u003ctd\u003e3x USB 3.2 2.0 (10 جيجابت\/ثانية)\u003cbr\u003e3x USB 2.0\u003c\/td\u003e\n\n\u003ctd\u003eUSB Type-A: 4x USB 3.2 Gen2\/ USB Type-C (UFP)\u003c\/td\u003e\n\n\u003ctd\u003e3x USB 3.2 2.0 (10 جيجابت\/ثانية)\u003cbr\u003e3x USB 2.0\u003c\/td\u003e\n\n\u003ctd colspan=\"2\"\u003eUSB Type-A: 4x USB 3.2 Gen2\/\u003cbr\u003eUSB Type-C (UFP)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eكاميرا CSI\u003c\/th\u003e\n\n\u003ctd\u003eما يصل إلى 4 كاميرات (8 عبر قنوات افتراضية**)\/\u003cbr\u003e8 مسارات MIPI CSI-2\/ D-PHY 1.2 (تصل إلى 20 جيجابت\/ثانية)\u003c\/td\u003e\n\n\u003ctd\u003eموصل كاميرا 2x MIPI CSI-2\u003c\/td\u003e\n\n\u003ctd\u003eما يصل إلى 4 كاميرات (8 عبر قنوات افتراضية**)\/\u003cbr\u003e8 مسارات MIPI CSI-2\/ D-PHY 1.2 (تصل إلى 20 جيجابت\/ثانية)\u003c\/td\u003e\n\n\u003ctd colspan=\"2\"\u003eموصل كاميرا 2x MIPI CSI-2\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eترميز الفيديو\u003c\/th\u003e\n\n\u003ctd colspan=\"5\"\u003eدعم 1080p30 بواسطة 1-2 نواة CPU\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eفك ترميز الفيديو\u003c\/th\u003e\n\n\u003ctd colspan=\"5\"\u003e1x 4K60 (H.265)\u003cbr\u003e2x 4K30 (H.265)\u003cbr\u003e5x 1080p60 (H.265)\u003cbr\u003e11x 1080p30 (H.265)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالعرض\u003c\/th\u003e\n\n\u003ctd\u003e1x 8K30 متعدد الأنماط DP 1.4a (+MST)\/\u003cbr\u003eeDP 1.4a\/HDMI 2.1\u003c\/td\u003e\n\n\u003ctd\u003eموصل 1x DisplayPort 1.2 (+MST)\u003c\/td\u003e\n\n\u003ctd\u003e1x 8K30 متعدد الأنماط DP 1.4a (+MST)\/\u003cbr\u003eeDP 1.4a\/HDMI 2.1\u003c\/td\u003e\n\n\u003ctd colspan=\"2\"\u003eموصل 1x DisplayPort 1.2 (+MST)\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eأخرى\u003c\/th\u003e\n\n\u003ctd\u003e3x UART, 2x SPI, 2x I2S, 4x I2C, 1x CAN, DMIC \u0026amp; DSPK, PWM, GPIO\u003c\/td\u003e\n\n\u003ctd\u003eرأس توسيع 40-Pin (UART, SPI, I2S, I2C, GPIO)، رأس أزرار 12-pin، رأس مروحة 4-pin، مقبس طاقة تيار مستمر\u003c\/td\u003e\n\n\u003ctd\u003e3x UART, 2x SPI, 2x I2S, 4x I2C, 1x CAN, DMIC \u0026amp; DSPK, PWM, GPIO\u003c\/td\u003e\n\n\u003ctd\u003eرأس توسيع 40-Pin (UART, SPI, I2S, I2C, GPIO)، رأس أزرار 12-pin، رأس مروحة 4-pin، مقبس طاقة تيار مستمر\u003c\/td\u003e\n\n\u003ctd\u003eرأس توسيع 40-Pin (UART, SPI, I2S, I2C, GPIO)، رأس أزرار 12-pin، رأس مروحة 4-pin، فتحة بطاقة TF، مقبس طاقة تيار مستمر\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالشبكات\u003c\/th\u003e\n\n\u003ctd\u003e1x GbE\u003c\/td\u003e\n\n\u003ctd\u003eموصل 1x GbE\u003c\/td\u003e\n\n\u003ctd\u003e1x GbE\u003c\/td\u003e\n\n\u003ctd colspan=\"2\"\u003eموصل 1x GbE\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003cth class=\"hilitColor\"\u003eالأبعاد\u003c\/th\u003e\n\n\u003ctd\u003e69.6 مم × 45 مم\u003cbr\u003eموصل 260-pin SO-DIMM\u003c\/td\u003e\n\n\u003ctd\u003e103 × 90.5 × 34 مم\u003c\/td\u003e\n\n\u003ctd\u003e69.6 مم × 45 مم\u003cbr\u003eموصل 260-pin SO-DIMM\u003c\/td\u003e\n\n\u003ctd\u003e103 × 90.5 × 34 مم\u003c\/td\u003e\n\n\u003ctd\u003e100 مم × 79 مم × 21 مم\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\u003ctr\u003e\n\n\u003ctd class=\"alignl\" colspan=\"6\"\u003e* تتشارك منافذ USB 3.2 و MGBE و PCIe في مسارات UPHY. راجع دليل تصميم المنتج للحصول على تكوينات UPHY المدعومة.\u003cbr\u003e** القنوات الافتراضية لـ Jetson Orin Nano قابلة للتغيير.\u003cbr\u003eراجع قسم ميزات البرامج في أحدث دليل لمطوري NVIDIA Jetson Linux للحصول على قائمة بالميزات المدعومة.\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\n\u003c\/div\u003e\n\n\u003ch1 style=\"text-align: center;\"\u003e \u003c\/h1\u003e\n\n\u003cdiv\u003e\n\n\u003ch2 class=\"richTitle hilitColor\"\u003eالموارد الموجودة على اللوحة\u003c\/h2\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-9.jpg\"\u003e\n\n\u003c\/div\u003e\n\n\u003ch1 style=\"text-align: center;\"\u003e \u003c\/h1\u003e\n\n\u003cdiv class=\"pdT\"\u003e\n\n\u003ch2 class=\"richTitle\"\u003eبرامج وتطبيقات النماذج الاحترافية\u003c\/h2\u003e\n\n\u003ctable style=\"width: 95%; margin: auto;\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; vertical-align: top; border: 0px;\"\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-11.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eبرامج N-VIDIA\u003c\/strong\u003e\u003cbr\u003eيتم دعم جميع وحدات N-VIDIA Jetson ومجموعات المطورين بواسطة نفس حزمة برامج N-VIDIA Jetson، بحيث يمكنك التطوير مرة واحدة والنشر في كل مكان. صُممت برامج Jetson لتوفير تسريع متكامل لتطبيقات الذكاء الاصطناعي وتسريع الوصول إلى السوق. وهذا يجلب تقنيات N-VIDIA القوية التي تشغل مراكز البيانات وعمليات النشر السحابية إلى الحافة.\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; vertical-align: top; border: 0px;\"\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-13.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eنماذج مدربة مسبقًا\u003c\/strong\u003e\u003cbr\u003eتحتوي العديد من تطبيقات الذكاء الاصطناعي على احتياجات مشتركة: التصنيف، اكتشاف الأشياء، ترجمة اللغات، تحويل النص إلى كلام، محركات التوصية، تحليل المشاعر، والمزيد. النماذج المدربة مسبقًا من كتالوج NGC™ محسنة الأداء وجاهزة للضبط الدقيق باستخدام مجموعة أدوات N-VIDIA TAO ومجموعات بيانات العملاء، مما يقلل الوقت والتكلفة لتطوير برمجيات الذكاء الاصطناعي للإنتاج.\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\u003cp class=\"pdT\" style=\"text-align: left;\"\u003e \u003c\/p\u003e\n\n\u003ch2 class=\"richTitle\"\u003e \u003c\/h2\u003e\n\n\u003ch2 class=\"richTitle\"\u003eمنصات N-VIDIA للروبوتات، وذكاء الكلام الاصطناعي، والمدن الذكية\u003c\/h2\u003e\n\n\u003cp class=\"richDesc\"\u003eمنصات برمجيات N-VIDIA بما في ذلك Isaac للروبوتات، وRiva لذكاء الكلام الاصطناعي، وMetropolis لتحليلات الفيديو، متاحة لتسريع التطبيقات المحددة عموديًا.\u003c\/p\u003e\n\n\u003ctable style=\"width: 95%; margin: auto;\"\u003e\n\n\u003ctbody\u003e\n\n\u003ctr\u003e\n\n\u003ctd style=\"text-align: center; vertical-align: top; border: 0px;\"\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-15.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eN-VIDIA Isaac\u003c\/strong\u003e\u003cbr\u003eتعمل الروبوتات على تحسين الكفاءة وجودة الحياة في صناعات مثل التصنيع، والخدمات اللوجستية، والرعاية الصحية، والخدمات. تعمل N-VIDIA Isaac™ على تسريع العملية من خلال تطوير الروبوتات والمحاكاة والنشر المعزز.\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; vertical-align: top; border: 0px;\"\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-17.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eN-VIDIA Riva\u003c\/strong\u003e\u003cbr\u003eN-VIDIA Riva هي مجموعة تطوير برمجيات (SDK) مسرعة بالكامل لبناء تطبيقات الذكاء الاصطناعي للمحادثة متعددة الوسائط باستخدام مسار تعلم عميق متكامل، وهي مناسبة للمهارات المحسنة في مهام الكلام، والرؤية، ومعالجة اللغات الطبيعية (NLP).\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\u003ctd style=\"text-align: center; vertical-align: top; border: 0px;\"\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-19.jpg\"\u003e\n\u003cp class=\"alignl pdTRBL\"\u003e\u003cstrong\u003eN-VIDIA Metropolis\u003c\/strong\u003e\u003cbr\u003eتتضمن N-VIDIA Metropolis إطار عمل للتطبيق، ومجموعة من أدوات المطورين، ونظام بيئي للشركاء. فهي تجمع بين البيانات المرئية والذكاء الاصطناعي لتحسين الكفاءة التشغيلية والسلامة عبر مجموعة واسعة من الصناعات.\u003c\/p\u003e\n\n\n\u003c\/td\u003e\n\n\n\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\n\n\n\u003c\/table\u003e\n\n\u003cdiv style=\"text-align: center;\"\u003e\n\n\u003ch2 class=\"richTitle\"\u003e \u003c\/h2\u003e\n\n\u003ch2 class=\"richTitle\"\u003eعرض المنتج\u003c\/h2\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-21.jpg\" style=\"margin-bottom: 16px; float: none;\"\u003e\n\n\u003c\/div\u003e\n\n\u003cdiv style=\"text-align: center;\"\u003e\n\n\u003ch2 class=\"richTitle\"\u003e \u003c\/h2\u003e\n\n\u003ch2 class=\"richTitle\"\u003eالأبعاد الخارجية\u003c\/h2\u003e\n\n\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/JETSON-ORIN-NANO-4G-DEV-KIT\/JETSON-ORIN-NANO-4G-DEV-KIT-details-size.jpg\" style=\"margin-bottom: 16px; float: none;\"\u003e\n\n\u003c\/div\u003e\n\n\u003cp style=\"text-align: left;\"\u003e \u003c\/p\u003e\n\n\u003ch2 class=\"richTitle\"\u003e \u003c\/h2\u003e\n\n\u003ch2 class=\"richTitle\" style=\"text-align: left;\"\u003eالموارد\u003c\/h2\u003e\n\n\u003cstrong\u003eWiki: \u003c\/strong\u003e\u003ca href=\"http:\/\/www.waveshare.com\/wiki\/Jetson_Orin_Nano\" id=\"tab-wiki\" target=\"_blank\"\u003ewww.waveshare.com\/wiki\/Jetson_Orin_Nano\u003c\/a\u003e\n\u003cp\u003e \u003c\/p\u003e\n\n\u003ch2 class=\"pdT\" style=\"text-align: left;\"\u003e \u003c\/h2\u003e\n\n\u003ch2 class=\"pdT\" style=\"text-align: left;\"\u003eمحتويات الحزمة:\u003c\/h2\u003e\n\n\u003cp style=\"text-align: left;\"\u003e\u003cstrong\u003eالوزن: \u003c\/strong\u003e\u003cspan\u003e0.572 كجم\u003c\/span\u003e\u003c\/p\u003e\n\n\u003cdiv class=\"std\"\u003e\n\n\u003col\u003e\n\n\u003cli style=\"text-align: left;\"\u003eمجموعة تطوير Waveshare Orin Nano:\n\u003col\u003e\n\n\u003cli style=\"text-align: left;\"\u003eوحدة Jetson Orin Nano عدد 1\u003c\/li\u003e\n\n\u003cli style=\"text-align: left;\"\u003eJETSON-ORIN-IO-BASE عدد 1\u003c\/li\u003e\n\n\u003cli style=\"text-align: left;\"\u003eمروحة تبريد عدد 1\u003c\/li\u003e\n\n\u003cli style=\"text-align: left;\"\u003eمحرك أقراص الحالة الصلبة NVMe سعة 240 جيجابايت (مجمع) عدد 1\u003c\/li\u003e\n\n\u003cli style=\"text-align: left;\"\u003eبطاقة شبكة لاسلكية (مجمعة) عدد 1\u003cbr\u003e\n\n\u003c\/li\u003e\n\n\n\u003c\/ol\u003e\n\n\n\u003c\/li\u003e\n\n\u003cli style=\"text-align: left;\"\u003eمحول طاقة عدد 1\u003c\/li\u003e\n\n\u003cli style=\"text-align: left;\"\u003eهيكل من الألومنيوم \/ المعدن \u003cspan style=\"color: rgb(255, 42, 0);\"\u003e\u003cstrong\u003eاختياري\u003c\/strong\u003e\u003c\/span\u003e\n\n\u003c\/li\u003e\n\n\n\u003c\/ol\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e","brand":"NVIDIA","offers":[{"title":"4GB \/ 3D Printed Plastic","offer_id":49736291844413,"sku":"SBC1116-4","price":65249.99,"currency_code":"INR","in_stock":true},{"title":"4GB \/ Aluminium","offer_id":50506971644221,"sku":"SBC1116-4A","price":69149.99,"currency_code":"INR","in_stock":true},{"title":"8GB \/ 3D Printed Plastic","offer_id":49736291877181,"sku":"SBC1116-8","price":70999.99,"currency_code":"INR","in_stock":true},{"title":"8GB \/ Aluminium","offer_id":50506971676989,"sku":"SBC1116-8A","price":74899.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/SBC1055-4.png?v=1752837866"},{"product_id":"agx-orin-32gb-h01","title":"Jetson AGX Orin 32GB H01 Kit with Jetson AGX Orin 32GB Module, 200 TOPs","description":"\u003cdiv class=\"relative\" id=\"product_info_970a857b53932\"\u003e\n\u003cdiv class=\"html_content_2981\"\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\"\u003eJetson AGX Orin 32GB H01 Kit is a powerful and compact intelligent kit to bring up to \u003cstrong\u003e200 TOPS\u003c\/strong\u003emodern AI performance to the edge, which offers up to \u003cstrong\u003e10X the performance of Jetson Xavier NX\u003c\/strong\u003e and up to \u003cstrong\u003e6X the performance of Jetson AGX Xavier\u003c\/strong\u003e. Combining the NVIDIA Ampere™ GPU architecture with 64-bit operating capability, AGX Orin integrates advanced multi-function video and image processing, and NVIDIA Deep Learning Accelerators.\u003c\/p\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\"\u003eThe full system includes one Jetson AGX Orin™ production module, a heatsink with a cooling fan, a case and a power adapter, while being the an alternative option for the Jetson AGX Orin Dev Kit. It has a carrier board including PCIe X16, GbE, 10GbE, 3x USB 3.2, HDMI 2.1, M.2 Key M, M.2 Key E, 2.4\/5GHz Wi-Fi, Bluetooth, 16 lane MIPI CSI-2, 40-Pin header, Jetson AGX Orin 32GB H01 Kit is preinstalled with Jetpack 5.0.2, simplifies development, and fits for deployment for edge AI solution providers working in video analytics, object detection, natural language processing, medical imaging, and robotics across industries of smart cities, security, industrial automation, smart factories.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eFeatures\u003c\/h2\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cul\u003e\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\n\u003cstrong\u003eBrilliant AI Performance for production: \u003c\/strong\u003eon-device processing with up to 200 TOPS AI performance with low power and low latency.\u003c\/li\u003e\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\n\u003cstrong\u003eHand-size edge AI device:\u003c\/strong\u003e compact size at 107mm x 106.4mm x 70.5mm, includes Jetson AGX Orin™ production module, a heatsink with a cooling fan, enclosure, and a power adapter.\u003c\/li\u003e\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\n\u003cstrong\u003eExpandable with rich I\/Os:\u003c\/strong\u003e PCIe X16, GbE, 10GbE, 3x USB 3.2, HDMI 2.1, M.2 Key M, M.2 Key E, 2.4\/5GHz Wi-Fi, Bluetooth, 16 lane MIPI CSI-2, 40-Pin header.\u003c\/li\u003e\n\u003cli class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\n\u003cstrong\u003eAccelerate solution to market:\u003c\/strong\u003e pre-installed JetPack 5.0.2, Linux OS BSP, support Jetson software and leading AI frameworks and software platforms.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eDescription\u003c\/h2\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\" style=\"text-align: center;\"\u003e\n\u003cp style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\"\u003eWith rich extension modules, industrial peripherals, and thermal management, Jetson AGX Orin 32GB H01 Kit is ready to help you accelerate and scale the next-gen AI product by deploying popular DNN models and ML frameworks to the edge and inferencing with high performance, for tasks like real-time classification and object detection, pose estimation, semantic segmentation, and natural language processing (NLP).\u003c\/p\u003e\n\u003cp style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\"\u003eAt Seeed Studio, you will find everything you want to work with the NVIDIA Jetson Platform – official NVIDIA Jetson Dev Kits, Seeed-designed carrier boards, edge devices, as well as accessories.\u003c\/p\u003e\n\u003cp style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.13 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eWe have prepared abundent \u003ca rel=\"noopener\" href=\"https:\/\/wiki.seeedstudio.com\/Jetson-AI-developer-tools\/\" target=\"_blank\"\u003eguides \u003c\/a\u003eto get started with NVIDIA Jetson using leading AI frameworks and software. For example, with \u003ca rel=\"noopener\" href=\"https:\/\/wiki.seeedstudio.com\/YOLOv5-Object-Detection-Jetson\/\" target=\"_blank\"\u003eDeepstream and TensorRT\u003c\/a\u003e, developers can deploy custom YOLOv5 models on Jetson AGX Orin.\u003c\/p\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/h2\u003e\n\u003ch2 style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eDeveloper Tools\u003c\/h2\u003e\n\u003ch3 style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003ePre-installed Jetpack for fast development and edge AI integration\u003c\/h3\u003e\n\u003cp style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/developer.nvidia.com\/embedded\/develop\/software\" target=\"_blank\"\u003eJetson software stack\u003c\/a\u003e begins with NVIDIA JetPack™ SDK which provides a full development environment and includes CUDA-X accelerated libraries and other NVIDIA technologies to kickstart your development. JetPack includes the Jetson Linux Driver package which provides the Linux kernel, bootloader, NVIDIA drivers, flashing utilities, sample filesystem, and toolchains for the Jetson platform. It also includes security features, over-the-air update capabilities, and much more.\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cimg data-original=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/image8.png\" height=\"950\" width=\"950\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/image8.png\" style=\"float: none;\"\u003e\u003c\/p\u003e\n\u003ch3 style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e \u003c\/h3\u003e\n\u003ch3 style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eComputer Vision and embedded machine learning\u003c\/h3\u003e\n\u003cul style=\"text-align: left;\"\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003ca rel=\"noopener\" href=\"https:\/\/developer.nvidia.com\/deepstream-sdk\" target=\"_blank\"\u003eNVIDIA DeepStream SDK\u003c\/a\u003e delivers a complete streaming analytics toolkit for AI-based multi-sensor processing and video and image understanding on Jetson.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003ca rel=\"noopener\" href=\"https:\/\/developer.nvidia.com\/tao-toolkit\" target=\"_blank\"\u003eNVIDIA TAO tool kit\u003c\/a\u003e, built on TensorFlow and PyTorch, is a low-code version of the NVIDIA TAO framework that accelerates the model training\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003ca rel=\"noopener\" href=\"https:\/\/alwaysai.co\/blog\/getting-started-with-the-jetson-nano-using-alwaysai\" target=\"_blank\"\u003ealwaysAI\u003c\/a\u003e: build, train, and deploy computer vision applications directly at the edge of reComputer. Get free access to 100+ pre-trained Computer Vision Models and train custom AI models in the cloud in a few clicks via enterprise subscription. Check out our \u003ca rel=\"noopener\" href=\"https:\/\/wiki.seeedstudio.com\/alwaysAI-Jetson-Getting-Started\/#object-detection-on-pre-loaded-video-file\" target=\"_blank\"\u003ewiki\u003c\/a\u003e guide to get started with alwaysAI.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003ca rel=\"noopener\" href=\"https:\/\/www.edgeimpulse.com\/\" target=\"_blank\"\u003eEdge Impulse\u003c\/a\u003e: the easiest embedded machine learning pipeline for deploying audio, classification, and object detection applications at the edge with zero dependencies on the cloud.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003ca rel=\"noopener\" href=\"https:\/\/blog.roboflow.com\/deploy-to-nvidia-jetson\/\" target=\"_blank\"\u003eRoboflow\u003c\/a\u003e provides tools to convert raw images into a custom-trained computer vision model of object detection and classification and deploy the model for use in applications. See the \u003ca rel=\"noopener\" href=\"https:\/\/docs.roboflow.com\/inference\/nvidia-jetson\" target=\"_blank\"\u003efull documentation\u003c\/a\u003e for deploying to NVIDIA Jetson with Roboflow.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003ca rel=\"noopener\" href=\"https:\/\/github.com\/ultralytics\/yolov5\" target=\"_blank\"\u003eYOLOv5 by Ultralytics\u003c\/a\u003e: use transfer learning to realize few-shot object detection with YOLOv5 which needs only a very few training samples. See our step-by-step \u003ca rel=\"noopener\" href=\"https:\/\/wiki.seeedstudio.com\/YOLOv5-Object-Detection-Jetson\/\" target=\"_blank\"\u003ewiki \u003c\/a\u003etutorials\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003ca rel=\"noopener\" href=\"https:\/\/deci.ai\/blog\/jetson-machine-learning-inference\/\" target=\"_blank\"\u003eDeci\u003c\/a\u003e: optimize your models on NVIDIA Jetson Nano. Check the \u003ca rel=\"noopener\" href=\"https:\/\/info.deci.ai\/benchmark-optimize-runtime-performance-nvidia-jetson\" target=\"_blank\"\u003ewebinar\u003c\/a\u003e at Deci of Automatically Benchmark and Optimize Runtime Performance on NVIDIA Jetson Nano and Xavier NX Devices\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3 style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eSpeech AI\u003c\/h3\u003e\n\u003cul style=\"text-align: left;\"\u003e\n\u003cli\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/developer.nvidia.com\/riva\" target=\"_blank\"\u003eNVIDIA® Riva\u003c\/a\u003e is a GPU-accelerated SDK for building Speech AI applications that are customized for your use case and deliver real-time performance.\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3 style=\"text-align: left;\" class=\"document\"\u003eRemote Fleet Management\u003c\/h3\u003e\n\u003cp style=\"text-align: left;\" dir=\"ltr\"\u003eEnable secure OTA and remote device management with \u003ca rel=\"noopener\" href=\"https:\/\/www.allxon.com\/\" target=\"_blank\"\u003eAllxon\u003c\/a\u003e. Unlock 90 days free trial with code H4U-NMW-CPK.\u003c\/p\u003e\n\u003ch3 style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eRobot and ROS Development\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eNVIDIA Isaac ROS GEMs are hardware-accelerated packages that make it easier for ROS developers to build high-performance solutions on NVIDIA hardware. Learn more about \u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/develop\/software\"\u003eNVIDIA Developer Tools\u003c\/a\u003e\n\u003c\/li\u003e\n\u003cli style=\"text-align: left;\" class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e\n\u003ca href=\"https:\/\/www.cogniteam.com\/nimbus\"\u003eCogniteam Nimbus\u003c\/a\u003e is a cloud-based solution that allows developers to manage autonomous robots more effectively. Nimbus platform supports NVIDIA® Jetson™ and ISAAC SDK and GEMs out-of-the-box. Check out our \u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/2022\/04\/21\/webinar-connect-your-ros-project-to-the-cloud-with-nimbus\/\"\u003ewebinar\u003c\/a\u003e on connecting your ROS Project to the Cloud with Nimbus.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\" class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eComparison among Jetson AGX Orin 32GB H01 Kit and AGX Orin Developer Kit\u003c\/h2\u003e\n\u003cdiv class=\"p_2981_table_wrapper\"\u003e\n\u003ctable class=\"p_2981_table\" cellpadding=\"1\"\u003e\n\u003ccolgroup\u003e \u003ccol width=\"117px\"\u003e \u003ccol width=\"227px\"\u003e \u003ccol width=\"250px\"\u003e \u003c\/colgroup\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003eSpecifications\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003eJetson AGX Orin 32GB H01 Kit\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/thinkrobotics.com\/products\/nvidia-jetson-agx-orin-developer-kit-64gb\" target=\"_blank\"\u003eJetson AGX Orin Developer Kit\u003c\/a\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eAI Performance\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e200 TOPS\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e275 TOPS\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eGPU\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1792-core NVIDIA Ampere GPU with 56 Tensor Cores\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eNVIDIA Ampere architecture with 2048 NVIDIA® CUDA® cores and 64 Tensor Cores\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eCPU\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e8-core NVIDIA Arm® Cortex A78AE v8.2 64-bit CPU 2MB L2 + 4MB L3\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e12-core Arm® Cortex®-A78AE v8.2 64-bit CPU 3MB L2 + 6MB L3\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eMemory\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e32 GB 256-bit LPDDR5 204.8 GB\/s\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eDL Accelerator\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e2 x NVDLA v2.0\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eVision Accelerator\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1 x PVA v2.0\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eStorage\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e64GB eMMC 5.1\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eVideo Encoder\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1x 4K60 | 3x 4K30 | 6x 1080p60 | 12x 1080p30 (H.265) 1x 4K60 | 2x 4K30 | 5x 1080p60 | 11x 1080p30 (H.264)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e2x 4K60 | 4x 4K30 | 8x 1080p60 | 16x 1080p30 (H.265)\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eVideo Decoder\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1x 8K30 | 2x 4K60 | 4x 4K30 | 9x 1080p60| 18x 1080p30 (H.265) 1x 4K60 | 2x 4K30 | 5x 1080p60 | 11x 1080p30 (H.264)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1x 8K30 | 3x 4K60 | 6x 4K30 | 12x 1080p60| 24x 1080p30 (H.265)\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eDisplay\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* HDMI 2.1\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1* DisplayPort 1.4a (+MST)\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eCamera\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1* 16 lane MIPI CSI-2 connector\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eNetworking\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* GbE\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* 10GbE\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1* 10GbE\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eUSB\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e2x USB 3.2 Type-A (Integrated USB 2.0), 1x USB 3.2 Type-C (Integrated USB 2.0)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e2x USB 3.2 Gen2 Type-Cwith USB-PD support\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e4x USB 3.2 Gen2 Type-A\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eUSB 2.0 Micro-B\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eM.2 Key M\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1* M.2 Key M\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eM.2 Key E\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* M.2 Key E (pre-installed WIFI+BT：8265.NGWMG.NV 949399)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-center pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\/\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eFan\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* 4-pin fan (5V PWM)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1* 4-pin fan\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003emicroSD card slot\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e1 * microSD card slot\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eAudio Jack\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* 3.5mm audio jack\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-center pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\/\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eRTC\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"477\" valign=\"\" align=\"\" colspan=\"2\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e2-pin RTC\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eRS485\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* RS485(3P 1.5mm pitch)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\/\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eRS232\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e1* RS232(3P 1.5mm pitch)\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\/\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eOthers\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e40-pin header, 1* SPI Bus(+3.3V Level), 6* GPIO(+3.3V Level), 1x CAN, Force Recovery, Reset and Power ON\/ OFF buttons, 12V\/2A 2-pin power output \u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e40-pin header, 12-pin automation header, 10-pin audio panel header, 10-pin JTAG header, Force Recovery, and Reset buttons\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003ePower Supply\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e+9---+20V DC Input @ 8A\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e19V via USB Type-C\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eMechanical\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e107mm x 106.4mm x 70.5mm\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e110mm x 110mm x 71.65mm\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"117\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eOperating Temperature\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"227\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cstrong\u003e-25 ⁰C to +70 ⁰C\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd width=\"250\" valign=\"\" align=\"\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e0 ⁰C to 35 ⁰C\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eHardware Overview\u003c\/h2\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eInterface-rich reference carrier board\u003c\/h3\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eJetson AGX Orin 32GB H01 Kit is a high-performance, interface-rich kit, providing PCIe X16, 1x 1GbE, 1x 10GbE, 3x USB 3.2, HDMI 2.1, M.2 Key M, and M.2 Key E, 2.4\/5GHz Wi-Fi, Bluetooth, 16 lane MIPI CSI-2, UART, 40-Pin header, and other rich peripheral interfaces.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eTake advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capabilities to all your embedded AI and edge systems.\u003c\/p\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan class=\"image-wrapper\"\u003e\u003cimg height=\"444\" width=\"950\" src=\"https:\/\/wdcdn.qpic.cn\/MTMxMDI3MDEwNTAxNTUxMDk_255393_5HLQ4e4U98vUwzeP_1673419554?w=1280\u0026amp;h=945.6512455516014\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan class=\"image-wrapper\"\u003e \u003c\/span\u003e\u003c\/p\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cspan class=\"image-wrapper\"\u003e\u003cimg height=\"514\" width=\"487\" src=\"https:\/\/wdcdn.qpic.cn\/MTMxMDI3MDEwNTAxNTUxMDk_492681_ZONmnIe8SsiuTMst_1673341714?w=815\u0026amp;h=861\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tips\"\u003e\n\u003cdiv class=\"right-desc\"\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e \u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e\u003cimg width=\"800\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/7_1_-114110207-Jetson-AGX-Orin-32GB-H01-Kit-size.jpg\"\u003e\u003c\/p\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003ePart List\u003c\/h2\u003e\n\u003cdiv class=\"p_2981_table_wrapper\"\u003e\n\u003ctable class=\"p_2981_table\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eJetson AGX Orin 32GB\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/td\u003e\n\u003ctd\u003e×1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eSeeed carrier board\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/td\u003e\n\u003ctd\u003e×1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eAluminum heatsink with fan\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/td\u003e\n\u003ctd\u003e×1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eAluminum case\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/td\u003e\n\u003ctd\u003e×1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e19V\/4.74A(Barrel Jack 5.5\/2.5mm) power adapter\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/td\u003e\n\u003ctd\u003e×1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/h2\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eDocuments\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tips\"\u003e\n\u003cdiv class=\"right-desc\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"relative\" id=\"product_info_d207d4b02efa4\"\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"html_content_2981\"\u003e\n\u003cdiv class=\"documents_list\"\u003e\n\u003cul\u003e\n\u003cli class=\"doc_item\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA\/Jetson-AGX-Orin-32GB-H01-Kit-Datasheet.pdf\" target=\"_blank\"\u003eJetson AGX Orin 32GB H01 Kit Datasheet.pdf\u003c\/a\u003e\u003c\/li\u003e\n\u003cli class=\"doc_item\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA\/NVIDIA-Jetson-Devices-and-carrier-boards-comparision.pdf\" target=\"_blank\"\u003eNVIDIA Jetson Devices and carrier boards comparision.pdf\u003c\/a\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"NVIDIA","offers":[{"title":"Default Title","offer_id":49842836078909,"sku":"SBC1119","price":223549.99,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/1-114110207-jetson-agx-orin-32gb-h01-kit-45fotn_1.jpg?v=1737739550"},{"product_id":"nvidia-jetson-agx-thor-developer-kit","title":"NVIDIA Jetson AGX Thor Developer Kit","description":"\u003ch2 style=\"text-align: center;\"\u003eNVIDIA Jetson Thor\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e\u003cstrong\u003eThe ultimate platform for physical AI and robotics.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/AGX-THOR2_jpg_effa758b-309d-491a-a606-721f74489fed.webp?v=1759570665\" alt=\"\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003eA Compact Powerhouse for Advanced AI and Robotics\u003c\/span\u003e\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003eNVIDIA Jetson Thor series modules give you the ultimate platform for physical AI and robotics, delivering up to 2070 FP4 TFLOPS of AI compute and 128 GB of memory with power configurable between 40 W and 130 W. They deliver over 7.5x higher AI compute than NVIDIA AGX Orin, with 3.5x better energy efficiency, enabling real-time multimodal perception, decision-making, and control, all for accelerating the development of intelligent, responsive, and highly sophisticated robotic systems.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eFeature\u003c\/h2\u003e\n\u003ctable cellpadding=\"10\" cellspacing=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center;\"\u003e\u003cstrong\u003eExtreme AI Performance for Robotics\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center;\"\u003ePowered by Jetson T5000 module with a Blackwell GPU (2560 cores, 96 Tensor Cores), delivering up to \u003cstrong\u003e2070 FP4 \/ 1035 FP8 TFLOPS \u003c\/strong\u003eIdeal for running generative AI models like LLMs, VLA (e.g., NVIDIA® Isaac™ GR00T N), ViT, and more.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center;\"\u003e\u003cstrong\u003eTransformer \u0026amp; Multimodal Optimization\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center;\"\u003eBuilt-in Transformer Engine and MIG (Multi-Instance GPU) support with \u003cstrong\u003e128 GB LPDDR5X (273 GB\/s)\u003c\/strong\u003e memory\u003cbr\u003eEnables efficient training and inference of transformer and multimodal models at the edge.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center;\"\u003e\u003cstrong\u003eReal-Time Processing\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center;\"\u003eEquipped with a \u003cstrong\u003e14-core Arm® Neoverse®-V3AE CPU\u003c\/strong\u003e\u003cbr\u003eDesigned for fast, deterministic real-time control in robotic applications.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center;\"\u003e\u003cstrong\u003eSensor \u0026amp; Network Integration\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center;\"\u003eSupports \u003cstrong\u003eup to 4× 25GbE\u003c\/strong\u003e high-speed connections\u003cbr\u003e140W power supply, and versatile I\/O including HDMI, DP, USB 3.2 \/ USB-C, CAN, and GbE Ideal for high-bandwidth, low-latency real-time sensor fusion and communication.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/image-kit.webp?v=1759562965\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eBenefits\u003c\/h2\u003e\n\u003ch4 style=\"text-align: center;\"\u003eBlackwell GPU, Sensor Processing, and Robotic AI Software Stack\u003c\/h4\u003e\n\u003ctable style=\"width: 90%; margin: auto; height: 547.699px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 318.068px;\"\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 50.0146%; height: 318.068px;\"\u003e\n\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-foundational-model-cognition.svg?v=1759567589\" alt=\"\" width=\"84\" height=\"84\"\u003e\u003cbr\u003e\n\u003cp\u003e\u003cstrong\u003eSupercomputer for Humanoids\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eAccelerate generative AI and large transformer models at the edge with the 2070 FP4 TFLOPS Blackwell GPU.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 49.7943%; height: 318.068px;\"\u003e\n\u003cp\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-speed.svg?v=1759567589\" alt=\"\" width=\"84\" height=\"84\"\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eHigh-Speed Sensor Processing\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eIngest high-speed sensor data for real-time performance with 4x 25 GbE networking, a camera offload engine, and a Holoscan Sensor Bridge.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 229.631px;\"\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 50.0146%; height: 229.631px;\"\u003e\n\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-robot-mimic.svg?v=1759567589\" alt=\"\" width=\"84\" height=\"84\"\u003e\u003cbr\u003e\n\u003cp\u003e\u003cstrong\u003eRobotic AI Software\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eDiscover a solution designed for humanoid robotics and physical AI applications, powered by the NVIDIA Isaac™ platform and GR00T foundational models.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 49.7943%; height: 229.631px;\"\u003e\n\u003cdiv style=\"text-align: start;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-containerized-security.svg?v=1759567589\" alt=\"\" width=\"84\" height=\"84\" style=\"display: block; margin-left: auto; margin-right: auto;\"\u003e\u003c\/div\u003e\n\u003cp\u003e\u003cstrong\u003eRobust Security\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eDeliver end-to-end safety and security across the compute platform, AI models, and the entire edge-to-cloud pipeline.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eSpecification\u003c\/h2\u003e\n\u003ctable cellpadding=\"8\" cellspacing=\"0\" border=\"1\" style=\"width: 100.065%; height: 1459.35px;\"\u003e\n\u003cthead\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003cth style=\"text-align: center; width: 15.408%; height: 39.2045px;\"\u003eSpecification\u003c\/th\u003e\n\u003cth style=\"text-align: center; width: 26.3461%; height: 39.2045px;\"\u003eJetson AGX Thor Developer Kit\u003c\/th\u003e\n\u003cth style=\"text-align: center; width: 22.7251%; height: 39.2045px;\"\u003eJetson T5000\u003c\/th\u003e\n\u003cth style=\"text-align: center; width: 24.4014%; height: 39.2045px;\"\u003eJetson T4000\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 39.2045px;\"\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 39.2045px;\"\u003e2070 TFLOPS (FP4—Sparse)\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 22.7251%; height: 39.2045px;\"\u003e2070 TFLOPS (FP4—Sparse)\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 39.2045px;\"\u003e1200 TFLOPS (FP4—Sparse)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.4091px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 78.4091px;\"\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 78.4091px;\"\u003e2560-core Blackwell GPU with 96 Tensor Cores\u003cbr\u003eMIG with 10 TPCs\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 22.7251%; height: 78.4091px;\"\u003e2560-core Blackwell GPU with 96 Tensor Cores\u003cbr\u003eMIG with 10 TPCs\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 78.4091px;\"\u003e1536-core Blackwell GPU with 64 Tensor Cores\u003cbr\u003eMIG with 6 TPCs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 39.2045px;\"\u003e\u003cstrong\u003eGPU Max Frequency\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"3\" style=\"text-align: center; width: 73.4726%; height: 39.2045px;\"\u003e1.57 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.4091px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 78.4091px;\"\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 78.4091px;\"\u003e14-core Arm® Neoverse®-V3AE\u003cbr\u003e1 MB L2\/core, 16 MB shared L3\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 22.7251%; height: 78.4091px;\"\u003e14-core Arm® Neoverse®-V3AE\u003cbr\u003e1 MB L2\/core, 16 MB shared L3\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 78.4091px;\"\u003e12-core Arm® Neoverse®-V3AE\u003cbr\u003e1 MB L2\/core, 16 MB shared L3\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 39.2045px;\"\u003e\u003cstrong\u003eCPU Max Frequency\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"3\" style=\"text-align: center; width: 73.4726%; height: 39.2045px;\"\u003e2.6 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 39.2045px;\"\u003e\u003cstrong\u003eVision Accelerator\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"3\" style=\"text-align: center; width: 73.4726%; height: 39.2045px;\"\u003e1× PVA v3\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 39.2045px;\"\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 39.2045px;\"\u003e128 GB LPDDR5X, 256-bit, 273 GB\/s\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 22.7251%; height: 39.2045px;\"\u003e128 GB LPDDR5X, 256-bit, 273 GB\/s\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 39.2045px;\"\u003e64 GB LPDDR5X, 256-bit, 273 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.4091px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 78.4091px;\"\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"text-align: center; width: 49.0713%; height: 78.4091px;\"\u003e1 TB NVMe M.2 Key M \u003cspan\u003eSlot\u003c\/span\u003e\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 78.4091px;\"\u003e\n\u003cspan\u003eSupports NVMe through PCIe\u003c\/span\u003e\u003cbr\u003e\u003cspan\u003eSupports SSD through USB3.2\u003c\/span\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.8068px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 58.8068px;\"\u003e\u003cstrong\u003eVideo Encode\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"3\" style=\"text-align: center; width: 73.4726%; height: 58.8068px;\"\u003e• 6× 4Kp60 (H.265), 12× 4Kp30 (H.265)\u003cbr\u003e• 24× 1080p60 (H.265), 50× 1080p30 (H.265)\u003cbr\u003e• 48× 1080p30 (H.264), 6× 4Kp60 (H.264)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.8068px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 58.8068px;\"\u003e\u003cstrong\u003eVideo Decode\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"3\" style=\"text-align: center; width: 73.4726%; height: 58.8068px;\"\u003e• 4× 8Kp30, 10× 4Kp60, 22× 4Kp30 (H.265)\u003cbr\u003e• 46× 1080p60, 92× 1080p30 (H.265)\u003cbr\u003e• 82× 1080p30, 4× 4Kp60 (H.264)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 208.409px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 208.409px;\"\u003e\u003cstrong\u003eCamera Support\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"3\" style=\"text-align: center; width: 73.4726%; height: 208.409px;\"\u003e\n\u003cp\u003e\u003cstrong\u003eJetson AGX Thor Developer Kit\u003cbr\u003eJetson T5000\u003c\/strong\u003e\u003cbr\u003e• HSB camera via QSFP\u003cbr\u003e• USB camera\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eJetson T4000\u003c\/strong\u003e\u003cbr\u003e• Up to 20 cameras via HSB\u003cbr\u003e• Up to 6 via 16x lanes MIPI CSI-2\u003cbr\u003e• Up to 32 using Virtual Channels\u003cbr\u003e• C-PHY 2.1 (10.25 Gbps), D-PHY 2.1 (40 Gbps)\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 98.0114px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 98.0114px;\"\u003e\u003cstrong\u003ePCIe\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"text-align: center; width: 49.0713%; height: 98.0114px;\"\u003e• M.2 Key M (x4 Gen5), M.2 Key E (x1 Gen5)\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 98.0114px;\"\u003e• Up to Gen5 (x8 lanes)\u003cbr\u003e• Root Port: C1 (x1), C3 (x2)\u003cbr\u003e• Root\/Endpoint: C2 (x1), C4 (x8), C5 (x4)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.8068px;\"\u003e\n\u003ctd style=\"width: 15.408%; height: 58.8068px;\"\u003e\u003cstrong\u003eUSB\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 58.8068px;\"\u003e• 2× USB-A (3.2 Gen2)\u003cbr\u003e• 2× USB-C (3.1)\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"text-align: center; width: 47.1265%; height: 58.8068px;\"\u003e• xHCI host controller\u003cbr\u003e• 3× USB 3.2\u003cbr\u003e• 4× USB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003ctd style=\"width: 15.408%; height: 39.2045px;\"\u003e\u003cstrong\u003eNetworking\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 39.2045px;\"\u003e1× 5 GbE RJ45\u003cbr\u003e1× QSFP28 (4× 25 GbE)\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 22.7251%; height: 39.2045px;\"\u003e4× 25 GbE\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 39.2045px;\"\u003e3× 25 GbE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.2045px;\"\u003e\n\u003ctd style=\"width: 15.408%; height: 39.2045px;\"\u003e\u003cstrong\u003eDisplay\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 39.2045px;\"\u003e1× HDMI 2.0b\u003cbr\u003e1× DisplayPort 1.4a\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"text-align: center; width: 47.1265%; height: 39.2045px;\"\u003e4× HDMI 2.1 shared\u003cbr\u003eVESA DP 1.4a (HBR2, MST)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 310.028px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 310.028px;\"\u003e\u003cstrong\u003eOther I\/O\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 310.028px;\"\u003e\n\u003cp\u003e• QSFP connector\u003cbr\u003e• M.2 Key E: WLAN\/BT, PCIe, USB2.0, UART, I2C, I2S\u003cbr\u003e• M.2 Key M: NVMe\u003cbr\u003e• PCIe x4, x2 lanes, I2C\u003cbr\u003e• 2× CAN headers, automation headers, LED, JTAG\u003cbr\u003e• 1x fan connector —12V, PWM, and Tach\u003cbr\u003eAudio panel header (2x 5-pin)\u003cbr\u003eMicrofit power jack\u003cbr\u003eRTC backup battery connector 2-pin\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 22.7251%; height: 310.028px;\"\u003e• 5× I2S \/ 2× AHUB\u003cbr\u003e• 2× DMIS\u003cbr\u003e• 4× UART, 4× CAN\u003cbr\u003e• 3× SPI, 13× I2C, 6× PWM\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 310.028px;\"\u003e• 5× I2S \/ 2× AHUB\u003cbr\u003e• 2× DMIS\u003cbr\u003e• 4× UART\u003cbr\u003e• 3× SPI, 13× I2C, 6× PWM\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.6023px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 19.6023px;\"\u003e\u003cstrong\u003ePower\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 19.6023px;\"\u003e40 W – 130 W\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 22.7251%; height: 19.6023px;\"\u003e40 W – 130 W\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 24.4014%; height: 19.6023px;\"\u003e40 W – 70 W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 98.0114px;\"\u003e\n\u003ctd style=\"text-align: center; width: 15.408%; height: 98.0114px;\"\u003e\u003cstrong\u003eMechanical\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 26.3461%; height: 98.0114px;\"\u003e243.19 mm x 112.40 mm x 56.88 mm\u003cbr\u003eThermal Transfer Plate (TTP) and optional fan or heat sink\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"text-align: center; width: 47.1265%; height: 98.0114px;\"\u003e100 mm x 87 mm\u003cbr\u003e699-pin B2B connector\u003cbr\u003eIntegrated Thermal Transfer Plate (TTP) with heatpipe\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e* \u003c\/span\u003eRefer to the Software Features section of the latest NVIDIA Jetson Linux Developer Guide for a list of supported features.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e**\u003c\/span\u003e Low-speed I\/O spec is subject to change.\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eApplication\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/image_app-1.webp?v=1759563172\"\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/image-app-2.webp?v=1759563172\"\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/image-app-3.webp?v=1759563172\"\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/image-app-4.webp?v=1759563171\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eGet Started with NVIDIA Jetson Thor\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe Jetson Thor AGX Developer Kit delivers unmatched performance and scalability for humanoids and physical AI. This video showcases its key features, specifications, and components, as well as how to power it on and initiate first boot. It also demonstrates some of the latest workflows, including Isaac GR00T N1, Video Search and Summarization (VSS), and NVIDIA Holoscan Sensor Bridge.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/jetson-thor-technical-brief.pdf?v=1759567474\" target=\"_blank\"\u003e\u003cstrong\u003eRead the Technical Brief\u003c\/strong\u003e\u003c\/a\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003ciframe title=\"Getting Started with the NVIDIA Jetson AGX Thor Developer Kit for Physical AI\" src=\"https:\/\/www.youtube.com\/embed\/iYT2haVIgSM\" height=\"355\" width=\"630\"\u003e\u003c\/iframe\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eDownload\u003c\/h2\u003e\n\u003ctable width=\"100%\" style=\"width: 100%; height: 28.5938px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 28.5938px;\"\u003e\n\u003ctd style=\"width: 66.065%; height: 28.5938px;\"\u003eDatasheet\u003c\/td\u003e\n\u003ctd style=\"width: 33.574%; text-align: right; height: 28.5938px;\"\u003e\u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Thor_Datasheet_f01b914b-d1d1-4c72-bfa8-0bb91b97c78d.pdf?v=1759569289\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch2 style=\"text-align: center;\"\u003e\u003cbr\u003e\u003c\/h2\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePackage Includes:\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e1 x NVIDIA Jetson AGX Thor Developer Kit\u003c\/p\u003e","brand":"NVIDIA","offers":[{"title":"Default Title","offer_id":50814727913789,"sku":"SBC1131","price":622499.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/image-kit-3_1.webp?v=1759568024"},{"product_id":"nvidia-dgx-spark","title":"NVIDIA DGX Spark","description":"\u003cblockquote\u003e\n\u003ch2 style=\"text-align: center;\"\u003eNVIDIA DGX Spark\u003c\/h2\u003e\n\u003c\/blockquote\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(123, 194, 61);\"\u003e\u003cstrong\u003eA Grace Blackwell AI supercomputer on your desk.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003ePowered by the NVIDIA GB10 Grace Blackwell Superchip, NVIDIA DGX™ Spark delivers one petaFLOP1 of AI performance in a power-efficient, compact form factor. With the NVIDIA AI software stack preinstalled and 128 GB of memory, developers can prototype, fine-tune, and inference the latest generation of reasoning AI models from DeepSeek, Meta, NVIDIA, Google, Qwen and others with up to 200 billion parameters locally.\u003c\/p\u003e\n\u003cblockquote\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eBuy either single or dual with free certified QSFP56 Cable (0.5m). Delivery starts from January 25, 2026 - buy yours today.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/blockquote\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/SPARK-FRONT_b0e25269-39ba-404a-a0b0-824871b9fc0a.png?v=1763456331\" alt=\"\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eFeatures\u003c\/h2\u003e\n\u003ch3 style=\"text-align: center;\"\u003eNVIDIA GPU, CPU, Networking, and AI Software Technologies\u003c\/h3\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 195.938px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 97.9688px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 97.9688px; text-align: center;\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-gh200-ffffff_1.svg?v=1763450000\" alt=\"\" width=\"80\" height=\"80\"\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eNVIDIA GB10 Superchip\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eExperience up to  1 petaFLOP  of AI performance at FP4 precision with the NVIDIA Grace Blackwell architecture.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 97.9688px; text-align: center;\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-ram-memory-ffffff_1.svg?v=1763450000\" alt=\"\" width=\"80\" height=\"80\"\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e128 GB of Coherent Unified System Memory\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eRun AI development and testing workloads with AI models up to 200 billion parameters at your desktop with a large, unified system memory.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 97.9688px; text-align: center;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 97.9688px;\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-cx-7-chip-ffffff_1.svg?v=1763449999\" alt=\"\" width=\"80\" height=\"80\"\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eNVIDIA ConnectX Networking\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eHigh-performance NVIDIA ConnectX™ networking enables the connection of two NVIDIA DGX Spark systems to work with AI models of up to 405 billion parameters.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 97.9688px;\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/m48-nim-ffffff_2.svg?v=1763450000\" alt=\"\" width=\"80\" height=\"80\"\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eNVIDIA AI Software Stack\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eUtilize a full-stack solution for generative AI workloads, encompassing NVIDIA tools, frameworks, libraries, and pre-trained models including NVIDIA NIM.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eWorkloads\u003c\/h2\u003e\n\u003ch3 style=\"text-align: center;\"\u003eAccelerate All AI Workloads\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003eDelivering the power of an AI supercomputer in a desktop-friendly size, NVIDIA DGX Spark is ideal for AI developer, researcher, and data scientist workloads.\u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 100%;\" colspan=\"2\"\u003e\n\u003ch4 style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(123, 194, 61);\"\u003ePrototyping\u003c\/span\u003e\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eDevelop, test, and validate AI models and applications.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eWith the NVIDIA AI software stack, NVIDIA DGX Spark provides the platform for developers to create, test, and validate AI models and AI-augmented applications and solutions. For final tuning or deployment, conveniently evaluate work for eventual migration to NVIDIA DGX cloud or other NVIDIA accelerated data centers or cloud infrastructures.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 50%;\"\u003e\n\u003ch4 style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(123, 194, 61);\"\u003eFine-Tuning\u003c\/span\u003e\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eFine-tune AI models up to 70 billion parameters.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eImprove the performance of pre-trained models by fine-tuning on NVIDIA DGX Spark. With 128GB of unified system memory, fine-tune models up to 70 billion parameters to customize AI models and solutions for specific needs and use cases.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 50%;\"\u003e\n\u003ch4 style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(123, 194, 61);\"\u003eInference\u003c\/span\u003e\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTest, validate, and inference with AI models.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eFifth-generation Tensor Cores with support for FP4 deliver up to 1 petaFLOP of AI computing performance, combined with 128GB of system memory, accelerate inference of state-of-the-art AI models to test, validate and deploy from your NVIDIA DGX Spark.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 50%;\"\u003e\n\u003ch4 style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(123, 194, 61);\"\u003eData Science\u003c\/span\u003e\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eHigh-performance data science at your desk.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eNVIDIA DGX Spark’s combination of 128GB of unified memory and 1 petaFLOP of parallel throughput maximizes performance of large, computationally complex data analytics and machine learning workflows at your desk.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; width: 50%;\"\u003e\n\u003ch4 style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(123, 194, 61);\"\u003eEdge Applications\u003c\/span\u003e\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eDevelop edge applications with NVIDIA AI frameworks.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eNVIDIA DGX Spark offers an exceptional platform for developing robotics, smart city, and computer vision solutions. NVIDIA frameworks include Isaac, Metropolis, and Holoscan. These frameworks and tools enable developers to take advantage of the power of NVIDIA DGX Spark to quickly develop edge applications.\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eNVIDIA DGX Spark Software\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eNVIDIA DGX Spark software stack accelerates AI and deep learning workloads while streamlining prototyping and development. It provides a scalable foundation for AI initiatives, enabling developers to harness NVIDIA’s powerful infrastructure to drive innovation and achieve transformative results.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/developer.nvidia.com\/topics\/ai\/dgx-spark\" target=\"_blank\"\u003eLearn More \u0026gt;\u003c\/a\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eSignificant Features and Benefits\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/webp_nvidia_project_digits_exploded_vew.jpg?v=1763450172\" alt=\"\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eA Grace Blackwell AI supercomputer on Your Desk\u003c\/h2\u003e\n\u003ch4 style=\"text-align: center;\"\u003e1. Based on NVIDIA Grace Blackwell Architecture\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003eAt the heart of DGX Spark is the new GB10 Grace Blackwell Superchip, based on the Grace Blackwell architecture and optimized for a desktop form factor. GB10 features a powerful Blackwell GPU with fifth-generation Tensor Cores and FP4 support, delivering up to 1000 AI TOPS of compute. GB10 also includes a high-performance Grace 20-core Arm CPU to supercharge data preprocessing and orchestration, speeding up model tuning and real-time inferencing. The GB10 Superchip uses the NVLink™-C2C to deliver a CPU+GPU coherent memory model with 5X the bandwidth of PCIe Gen 5.\u003c\/p\u003e\n\u003ch4 style=\"text-align: center;\"\u003e2. Work With the Latest Generation of Large-Parameter Generative AI Models\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003eWith 128 GB of unified system memory and support for the FP4 data format, DGX Spark can support AI models of up to 200B parameters, enabling AI developers to prototype, fine-tune and inference the latest generation of AI reasoning models—such as DeepSeek R1 distilled versions up to 70 billion parameters—on their desktop. With built-in NVIDIA ConnectX™ network technology, two DGX Spark systems can be connected to work on even larger models such as Llama 3.1 405B.\u003c\/p\u003e\n\u003ch4 style=\"text-align: center;\"\u003e3. Develop Locally, Deploy Anywhere at Scale\u003c\/h4\u003e\n\u003cp style=\"text-align: center;\"\u003eDGX Spark provides developers with a powerful, experimentation ground for prototyping models and AI applications, freeing up valuable compute resources in their cluster environments better suited for training and deploying production models. Leveraging the NVIDIA AI platform software architecture makes it possible for DGX Spark users to seamlessly move their models from their desktop to DGX Cloud or any accelerated cloud or data center infrastructure with virtually no code changes, making it easier than ever to prototype, fine-tune, and iterate.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eSpecifications\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eArchitecture\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eNVIDIA Grace Blackwell\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eGPU\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eBlackwell Architecture\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eCPU\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e20 core Arm, 10 Cortex-X925 + 10 Cortex-A725 Arm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eCUDA Cores\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eBlackwell Generation\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eTensor Cores\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e5th Generation\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eRT Cores\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e4th Generation\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eTensor Performance\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e1 PFLOP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eSystem Memory\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e128 GB LPDDR5x, coherent unified system memory\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eMemory Interface\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e256-bit\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eMemory Bandwidth\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e273 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eStorage\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e4 TB NVME.M2 with self-encryption\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eUSB\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e4x USB TypeC\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eEthernet\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e1x RJ-45 connector, 10 GbE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eNIC\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eConnectX-7 NIC @ 200 Gbps\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eWi-Fi\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eWiFi 7\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eBluetooth\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eBT 5.4\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eAudio-output\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eHDMI multichannel audio output\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003ePower Supply\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e240 Watts\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eDisplay Connectors\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e1x HDMI 2.1a\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eNVENC | NVDEC\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e1x | 1x\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eOS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003eNVIDIA DGX™ OS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eSystem Dimensions\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e150 mm L × 150 mm W × 50.5 mm H\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.1598%;\"\u003eSystem Weight\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.8402%;\"\u003e1.2 kg\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cem\u003e* preliminary specifications, subject to change. 1 Theoretical FP4 TOPS using the sparsity feature.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eResources\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eDatasheet\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/workstation-datasheet-dgx-spark-gtc25-spring-nvidia-us-3716899-web.pdf?v=1763452160\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePackage Contains\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 49.1876px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; text-align: center;\"\u003eNVIDIA® DGX Spark™\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; text-align: center;\"\u003eQuick Start Card\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 10px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 10px; text-align: center;\"\u003eSupport Card\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 0px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 0px; text-align: center;\"\u003ePower Supply\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cbr\u003e\u003c\/p\u003e","brand":"NVIDIA","offers":[{"title":"Single Unit","offer_id":51141865308477,"sku":"SBC1142","price":579499.99,"currency_code":"INR","in_stock":true},{"title":"Dual Unit with 200G QSFP56 Cable","offer_id":51141865341245,"sku":"SBC1142-D","price":1168999.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/SPARK-3QTR-Right.png?v=1763456416"},{"product_id":"thinkrobotics-jetson-orin-nx-deployment-kit-commercial-version","title":"ThinkRobotics Jetson Orin NX Deployment Kit (Commercial Version)","description":"\u003cdiv class=\"document\"\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\" style=\"text-align: center;\"\u003eThinkRobotics Edge AI Device with NVIDIA Jetson Orin™ NX 8GB \/ 16GB module\u003c\/h2\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\" style=\"text-align: center;\"\u003eThinkRobotics Edge AI Device is built with Jetson Orin NX 8GB or 16GB - a powerful and compact intelligent edge box to bring up to 100 TOPS modern AI performance to the edge, which offers up to 5X the performance of Jetson Xavier NX and up to 3X the performance of Jetson AGX Xavier. Combining the NVIDIA Ampere™ GPU architecture with 64-bit operating capability, Orin NX integrates advanced multi-function video and image processing, and NVIDIA Deep Learning Accelerators.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\" style=\"text-align: center;\"\u003eThe full system includes one NVIDIA Jetson Orin™ NX 8GB or 16GB production module, \u003cstrong\u003eWaveshare Jetson Orin Nano\/NX Development Board carrier board, a \u003ca href=\"https:\/\/thinkrobotics.com\/products\/official-cooling-fan-for-jetson-orin-online\" target=\"_blank\"\u003eheatsink\u003c\/a\u003e, RTL8822CE Wireless NIC - Wi-Fi, a power adapter installed in a 3D printed carbon fiber case or a metal case.\u003c\/strong\u003e The device is preinstalled with JetPack 6.2 on the included 240GB NVMe SSD, simplifies development, and fits for deployment for edge AI solution providers working in video analytics, object detection, natural language processing, medical imaging, and robotics across industries of smart cities, security, industrial automation, smart factories.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003c\/div\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003eFeatures\u003cstrong\u003e\u003c\/strong\u003e\n\u003c\/h2\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003eBrilliant AI performance for production with on-device processing delivering up to 100 TOPS AI performance with low power consumption and low latency.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003e\u003cstrong\u003eCompact Edge AI Device\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003eHand-size edge AI device with compact dimensions of 130mm × 120mm × 58.5mm. Includes NVIDIA Jetson Orin™ NX 16GB production module, cooling fan with heatsink, enclosure, and power adapter. Supports desktop and wall mounting for flexible deployment.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003e\u003cstrong\u003eExpandable I\/O\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003eExpandable with rich I\/Os (Waveshare SBC2152): 4 × USB 3.2 Type-A, 1 × USB Type-C (system burning), DisplayPort for 4K output, RJ45 Gigabit Ethernet, 2 × 4-Lane CSI, M.2 Key E, 2 × M.2 Key M (for NVMe SSDs), and 40-Pin GPIO.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003e\u003cstrong\u003eSoftware \u0026amp; Development\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003eAccelerate solution deployment with pre-installed JetPack including NVIDIA JetPack™ 5.1 on the bundled 240GB NVMe SSD. Includes Linux OS BSP and supports Jetson software, leading AI frameworks, and development platforms.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003e\u003cstrong\u003eCertifications\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center;\"\u003eComprehensive certifications including FCC, CE, and RoHS compliance.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e \u003c\/p\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003eDescription\u003c\/h2\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\" style=\"text-align: center;\"\u003eWith rich extension modules, industrial peripherals, and thermal management, the Edge AI Device with the Waveshare SBC2152 carrier board is ready to help you accelerate and scale the next-gen AI product by deploying popular DNN models and ML frameworks to the edge and inferencing with high performance, for tasks like real-time classification and object detection, pose estimation, semantic segmentation, and natural language processing (NLP).\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\" style=\"text-align: center;\"\u003eThe \u003cstrong\u003eWaveshare Jetson Orin Nano\/NX Development Board\u003c\/strong\u003e provides almost the same peripheral interfaces, size and thickness as the official Jetson Orin Nano Developer Kit, making it ideal for users to develop and deploy their AI applications.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.13 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003eGuides and resources are available to get started with NVIDIA Jetson using leading AI frameworks and software. For example, with \u003ca href=\"https:\/\/wiki.seeedstudio.com\/YOLOv5-Object-Detection-Jetson\/\" target=\"_blank\"\u003eDeepstream and TensorRT\u003c\/a\u003e, developers can deploy custom YOLOv5 models on Jetson Orin at over 100FPS\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.13 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e \u003c\/p\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.13 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003eDevelopers Tools\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003ePre-installed Jetpack for fast development and edge AI integration\u003c\/h3\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\" style=\"text-align: center;\"\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/embedded\/develop\/software\" target=\"_blank\"\u003eJetson software stack\u003c\/a\u003e begins with NVIDIA JetPack™ SDK which provides a full development environment and includes CUDA-X accelerated libraries and other NVIDIA technologies to kickstart your development. JetPack includes the Jetson Linux Driver package which provides the Linux kernel, bootloader, NVIDIA drivers, flashing utilities, sample filesystem, and toolchains for the Jetson platform. It also includes security features, over-the-air update capabilities, and much more.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\" style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003eComputer Vision and embedded machine learning\u003c\/h3\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse; height: 450.656px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 39.1875px;\"\u003e\u003cstrong\u003ePlatform \/ Toolkit\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 39.1875px;\"\u003e\u003cstrong\u003eDescription\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003e\u003cstrong\u003eNVIDIA DeepStream SDK\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003eNVIDIA DeepStream SDK provides a complete streaming analytics toolkit for AI-based multi-sensor processing, enabling video and image understanding on NVIDIA Jetson platforms.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003e\u003cstrong\u003eNVIDIA TAO Toolkit\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003eNVIDIA TAO Toolkit, built on TensorFlow and PyTorch, offers a low-code framework that accelerates AI model training and optimization for deployment on edge devices.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.375px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 78.375px;\"\u003e\u003cstrong\u003ealwaysAI\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 78.375px;\"\u003ealwaysAI enables developers to build, train, and deploy computer vision applications directly at the edge of reComputer devices. It provides access to 100+ pre-trained computer vision models and supports cloud-based training of custom AI models through enterprise subscription.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003e\u003cstrong\u003eEdge Impulse\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003eEdge Impulse provides an embedded machine learning pipeline for deploying audio processing, classification, and object detection applications at the edge with zero dependency on the cloud.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003e\u003cstrong\u003eRoboflow\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003eRoboflow offers tools to convert raw images into custom-trained computer vision models for object detection and classification, and deploy them for use in applications on NVIDIA Jetson devices.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003e\u003cstrong\u003eYOLOv5 (Ultralytics)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 58.7812px;\"\u003eYOLOv5 by Ultralytics supports transfer learning for few-shot object detection, allowing models to be trained using a small number of samples for rapid deployment.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); height: 39.1875px; text-align: center;\"\u003e\u003cstrong\u003eDeci\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); height: 39.1875px; text-align: center;\"\u003eDeci provides tools to benchmark and optimize AI model runtime performance on NVIDIA Jetson platforms such as Jetson Nano and Xavier NX.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\" class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003e \u003c\/p\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003eSpeech AI\u003c\/h3\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003e\u003ca href=\"https:\/\/developer.nvidia.com\/riva\" target=\"_blank\"\u003eNVIDIA® Riva\u003c\/a\u003e is a GPU-accelerated SDK for building Speech AI applications that are customized for your use case and deliver real-time performance.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch3 class=\"document\" style=\"text-align: center;\"\u003eRemote Fleet Management\u003c\/h3\u003e\n\u003cp dir=\"ltr\" style=\"text-align: center;\"\u003eEnable secure OTA and remote device management with \u003ca href=\"https:\/\/www.allxon.com\/\" target=\"_blank\"\u003eAllxon\u003c\/a\u003e. Unlock 90 days free trial with code H4U-NMW-CPK.\u003c\/p\u003e\n\u003cp dir=\"ltr\" style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\" style=\"text-align: center;\"\u003eRobot and ROS Development\u003c\/h3\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse; height: 215.531px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 39.1875px;\"\u003e\u003cstrong\u003ePlatform \/ Toolkit\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 39.1875px;\"\u003e\u003cstrong\u003eDescription\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.375px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 78.375px;\"\u003e\u003cstrong\u003eNVIDIA Isaac ROS GEMs\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 78.375px;\"\u003eNVIDIA Isaac ROS GEMs are hardware-accelerated packages designed to help ROS developers build high-performance robotic solutions on NVIDIA hardware. These packages provide optimized algorithms and tools to accelerate perception, navigation, and robotics workflows on NVIDIA Jetson platforms.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 97.9688px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 97.9688px;\"\u003e\u003cstrong\u003eCogniteam Nimbus\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; height: 97.9688px;\"\u003eCogniteam Nimbus is a cloud-based platform that enables developers to manage and deploy autonomous robots efficiently. The Nimbus platform supports NVIDIA® Jetson™ devices and NVIDIA ISAAC SDK and GEMs out-of-the-box, allowing seamless integration between robotics applications and cloud infrastructure.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cdiv class=\"document\" style=\"text-align: center;\"\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"document\"\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-7.5pt\"\u003e   \u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003ch2 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eHardware Overview\u003c\/h2\u003e\n\u003ch3 class=\"paragraph text-align-type-left pap-line-1.7 pap-line-rule-auto pap-spacing-before-0pt pap-spacing-after-0pt\"\u003eWaveshare Jetson Orin Nano\/NX Development Board\u003c\/h3\u003e\n\u003cp\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/JETSON-ORIN-IO-BASE-details-13.jpg?v=1773381468\" alt=\"\"\u003e\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eThe Waveshare carrier board for Jetson Orin Nano\/NX provides a comprehensive set of interfaces, offering a robust platform for edge AI development. It is compatible with both the Jetson Orin Nano and Jetson Orin NX modules. Key features include:\u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 98.75%; height: 800px; margin-left: auto; margin-right: auto;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 52.0646%; text-align: center;\"\u003e\n\u003cstrong\u003e1. 260PIN DO-DIMM socket\u003c\/strong\u003e\u003cbr\u003eFor connecting Jetson Orin Nano\/NX module\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 47.9354%; text-align: center;\"\u003e\n\u003cstrong\u003e9. USB Type-C port\u003c\/strong\u003e\u003cbr\u003eFor system burning and data communication\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.375px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 78.375px; width: 52.0646%; text-align: center;\"\u003e\n\u003cstrong\u003e2. 12PIN header\u003c\/strong\u003e\u003cbr\u003eAdapting pins for power supply, reset button, force recovery setting, serial port debug, auto power-up enable, and power indicator functions\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 78.375px; width: 47.9354%; text-align: center;\"\u003e\u003cstrong\u003e10. 40PIN header\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 39.1875px; width: 52.0646%; text-align: center;\"\u003e\u003cstrong\u003e3. Power button\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 39.1875px; width: 47.9354%; text-align: center;\"\u003e\u003cstrong\u003e11. 4PIN PWM fan header\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 39.1875px; width: 52.0646%; text-align: center;\"\u003e\n\u003cstrong\u003e4. 2 × 22PIN CSI camera interfaces\u003c\/strong\u003e\u003cbr\u003e2 × MIPI CSI 4-lane camera interfaces\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 39.1875px; width: 47.9354%; text-align: center;\"\u003e\n\u003cstrong\u003e12. M.2 Key E\u003c\/strong\u003e\u003cbr\u003eFor connecting wireless NIC\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 52.0646%; text-align: center;\"\u003e\n\u003cstrong\u003e5. DC Power jack\u003c\/strong\u003e\u003cbr\u003eSupports wide range 9V–19V power supply, compatible with 5.5 × 2.5 mm male plug\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 47.9354%; text-align: center;\"\u003e\n\u003cstrong\u003e13. 2 × M.2 Key M\u003c\/strong\u003e\u003cbr\u003eFor connecting NVMe solid state drives\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 39.1875px; width: 52.0646%; text-align: center;\"\u003e\n\u003cstrong\u003e6. HDMI display interface\u003c\/strong\u003e\u003cbr\u003eHDMI output\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 39.1875px; width: 47.9354%; text-align: center;\"\u003e\n\u003cstrong\u003e14. RTC backup battery header\u003c\/strong\u003e\u003cbr\u003ePH1.25 2PIN\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 52.0646%; text-align: center;\"\u003e\n\u003cstrong\u003e7. 4 × USB 3.2 Gen2 Type-A ports\u003c\/strong\u003e\u003cbr\u003eSupports up to 10 Gbps data transmission\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 47.9354%;\"\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 52.0646%; text-align: center;\"\u003e\u003cstrong\u003e8. RJ45 Gigabit Ethernet port\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; vertical-align: top; height: 58.7812px; width: 47.9354%;\"\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003eTake advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capabilities to all your embedded AI and edge systems.\u003c\/p\u003e\n\u003cp class=\"paragraph text-align-type-left pap-line-1.3 pap-line-rule-auto pap-spacing-before-3pt pap-spacing-after-3pt\"\u003e \u003c\/p\u003e\n\u003ch2\u003ePart List\u003c\/h2\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse; height: 137.157px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 52.0631%; height: 19.5938px;\"\u003eNVIDIA Jetson Orin™ NX \u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cstrong\u003e16GB \/ 8GB\u003c\/strong\u003e\u003c\/span\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 47.9369%; height: 19.5938px;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 52.0631%; height: 19.5938px;\"\u003eWaveshare Carrier Board\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 47.9369%; height: 19.5938px;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 52.0631%; height: 19.5938px;\"\u003e240GB NVMe SSD\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 47.9369%; height: 19.5938px;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 52.0631%; height: 19.5938px;\"\u003eAluminum Heatsinks with Fan\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 47.9369%; height: 19.5938px;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 52.0631%; height: 19.5938px;\"\u003e3D Printed Case \/ Aluminium Case\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 47.9369%; height: 19.5938px;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 52.0631%; height: 19.5938px;\"\u003eWi-Fi Module with Antenna\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 47.9369%; height: 19.5938px;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 52.0631%; height: 19.5938px;\"\u003e12V \/ 5A Power Adapter\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); text-align: center; width: 47.9369%; height: 19.5938px;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch2\u003e \u003c\/h2\u003e\n\u003ch2\u003eFAQ\u003c\/h2\u003e\n\u003ch3\u003eWhat type of RTC is recommended for RTC socket?\u003c\/h3\u003e\n\u003cp\u003eThe Waveshare SBC2152 provides an RTC backup battery header. CR1220 and ML1220 batteries are typically compatible for RTC backup.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eDocumentations\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA\/reComputer-J401x-datasheet.pdf\" target=\"_blank\"\u003e\u003c\/a\u003e\n\u003c\/h2\u003e\n\u003cdiv class=\"product documents-tab\"\u003e\n\u003cdiv class=\"value documents-info\"\u003e\n\u003cp\u003e\u003ca href=\"https:\/\/www.waveshare.com\/wiki\/JETSON-ORIN-NX-8G-DEV-KIT\" rel=\"noopener\" target=\"_blank\"\u003ehttps:\/\/www.waveshare.com\/wiki\/JETSON-ORIN-NX-8G-DEV-KIT\u003c\/a\u003e\u003c\/p\u003e\n\u003cp\u003e\u003ca href=\"https:\/\/www.waveshare.com\/wiki\/JETSON-ORIN-NX-16G-DEV-KIT\"\u003ehttps:\/\/www.waveshare.com\/wiki\/JETSON-ORIN-NX-16G-DEV-\u003c\/a\u003e\u003ca href=\"https:\/\/www.waveshare.com\/wiki\/JETSON-ORIN-NX-16G-DEV-KIT\" rel=\"noopener\" target=\"_blank\"\u003eKIT\u003c\/a\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"NVIDIA","offers":[{"title":"8GB \/ 3D Printed Plastic","offer_id":51153153392957,"sku":"SBC1149-8","price":103049.99,"currency_code":"INR","in_stock":true},{"title":"8GB \/ Aluminium","offer_id":51153153425725,"sku":"SBC1149-8A","price":106949.99,"currency_code":"INR","in_stock":true},{"title":"16GB \/ 3D Printed Plastic","offer_id":51153153458493,"sku":"SBC1149-16","price":143599.99,"currency_code":"INR","in_stock":true},{"title":"16GB \/ Aluminium","offer_id":51153153491261,"sku":"SBC1149-16A","price":146599.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/SBC1055-3_543c67ef-5406-44af-90c6-1d9a19e97e72.png?v=1774596861"},{"product_id":"sima-ai-modalix-deployment-kit","title":"SiMa.ai Modalix Deployment Kit  : (SW license extra)","description":"\u003ch2 style=\"text-align: center;\"\u003eModalix Deployment Kit\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe SiMa.ai MLSoC Modalix Development Kit (DevKit) is a complete hardware and software platform for evaluating and prototyping intelligent Physical AI applications using the latest Modalix System-on-Module (SoM).\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eDesigned for rapid deployment, this kit enables seamless development, benchmarking, and proof-of-concept creation with SiMa.ai’s Palette software, offering best-in-class performance-per-watt in a compact form factor. Ideal for industrial, robotics, and vision-based and LLM-based applications, this kit supports real-time inferencing across computer vision, transformer models, and GenAI workloads.\u003c\/p\u003e\n\u003cdiv style=\"display: grid; grid-template-columns: 1fr; gap: 24px; margin-bottom: 24px;\"\u003e\n\u003c!-- Cards Container --\u003e\n\u003cdiv class=\"feature-grid\"\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eBuild, test, and deploy AI apps fast\u003c\/h3\u003e\n\u003cp\u003eLaunch edge AI applications in just minutes with our streamlined workflow\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003ePrototype smart, autonomous systems\u003c\/h3\u003e\n\u003cp\u003eDesign Physical AI, robotics, and sensor-based apps with ease\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eExplore demos, models, and docs\u003c\/h3\u003e\n\u003cp\u003eAccess ready-to-run examples, pretrained models, and full guides\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eComplete kit with all essentials\u003c\/h3\u003e\n\u003cp\u003eFast deployment includes software, cables, tools, and power—no extras needed\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eDeploy your models seamlessly with industry-standard compatibility\u003c\/h3\u003e\n\u003cp\u003eDeploy your models seamlessly with industry-standard compatibility\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cstyle\u003e\n.feature-grid {\n  display: grid;\n  gap: 24px;\n  grid-template-columns: repeat(1, 1fr);\n}\n\n\/* Tablet *\/\n@media (min-width: 768px) {\n  .feature-grid {\n    grid-template-columns: repeat(2, 1fr);\n  }\n}\n\n\/* Desktop *\/\n@media (min-width: 1024px) {\n  .feature-grid {\n    grid-template-columns: repeat(5, 1fr);\n  }\n}\n\n.card {\n  background: #fff;\n  border-radius: 16px;\n  padding: 32px 24px;\n  text-align: center;\n  box-shadow: 0 8px 24px rgba(0,0,0,0.08);\n}\n\n.card h3 {\n  margin-bottom: 12px;\n}\n\n.card p {\n  margin: 0;\n}\n\u003c\/style\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePowered by MLSoC Modalix SoM\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe MLSoC Modalix System-on-Module (SoM) provides the proven performance of the Modalix MLSoC architecture in a compact, deployment-ready form factor, purpose-built to Scale Physical AI applications.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe Modalix innovative system architecture seamlessly integrates a set of compute engines and peripherals, delivering best-in-class performance per watt for advanced workloads, including multimodal Transformers, Large Language Models (LLMs), Large Multimodal Models (LMMs), and Generative AI (GenAI). It also maintains full support for legacy convolutional neural networks (CNNs) and traditional\u003cbr\u003ecomputer vision algorithms, ensuring broad compatibility across both modern and established ML pipelines.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe Modalix SoM offers the best-in-class performance per watt.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg alt=\"\" src=\"https:\/\/sima.ai\/wp-content\/uploads\/2025\/08\/som-chips-with-bg.png\" class=\"object-contain\" decoding=\"async\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eMLSoC Modalix SoM Feature Highlights\u003cbr\u003e\n\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eMachine Learning Accelerator (MLA)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e50 TOPs (BF16, INT8, INT16)\u003cbr\u003eSupports LLMs, neural networks, and GenAI\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eApplication Compute Unit (ACU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e8 × ARM Cortex-A65 @ 1.4 GHz\u003cbr\u003e32K Dhrystone MIPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e32 GB or 8 GB on-board 128-bit LPDDR5 (6400 Mbps) system memory\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eBoot and Security Unit (BSU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eSecure boot with boot code authentication and encryption\u003cbr\u003eSecure key storage and management\u003cbr\u003eSecurity engine for user code\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eVideo Codec\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eDecode H.264 \/ H.265 \/ AV1 up to 4K60\u003cbr\u003eEncode H.264 \/ H.265 up to 4K60\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eComputer Vision Unit (CVU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e4-core Synopsys EV74 DSP @ 1 GHz\u003cbr\u003e720 GOPS (16-bit)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eLow-Latency ISP\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eARM Mali-C-1 @ 1.2 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eDisplay Connectivity\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eHDMI 1.4 port with 4K resolution\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003ePeripherals\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e4 × 2-lane MIPI CSI-2\u003cbr\u003e4 × PCIe Gen5 RC \u0026amp; EP\u003cbr\u003e1 × 1Gb Ethernet PHY\u003cbr\u003e3 × USB 3.0\u003cbr\u003e4 × I2C, 3 × UART, 14 × GPIO\u003cbr\u003e2 × SPI\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eExternal NVMe via PCIe x4\u003cbr\u003eExternal SSD via USB 3.0\u003cbr\u003e16 GB eMMC flash\u003cbr\u003e64 MB QSPI flash\u003cbr\u003e128 KB EEPROM\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003ePower Supply\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eFlexible 5–20 V power input\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eForm Factor\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e69.6 mm × 45 mm\u003cbr\u003e260-pin SO-DIMM connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eOperating Temperature\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e\n\u003cstrong\u003eCommercial SoM: \u003c\/strong\u003e 0°C to +60°C\u003cbr\u003e\u003cstrong\u003e    Industrial SoM:  \u003c\/strong\u003e-40°C to +85°C\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eDevelopment Flow\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003ePhase\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDescription\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDetails\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eEvaluate\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eUse Palette to compile and run models, assess performance (FPS, latency, compute utilization), and monitor system metrics.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid #000; padding: 8px;\"\u003e\n\u003cul style=\"margin: 0; padding-left: 18px;\"\u003e\n\u003cli\u003eDocker-based toolchain\u003c\/li\u003e\n\u003cli\u003eARM cross-compiler\u003c\/li\u003e\n\u003cli\u003ePlatform image build \u0026amp; deploy tools\u003c\/li\u003e\n\u003cli\u003eIntegrated KPIs and performance feedback\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003ePrototype\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eDevelopers can rapidly prototype functional pipelines using SiMa.ai’s Python APIs.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eEnables fast bring-up of custom ML workflows directly on the hardware without complex embedded optimization.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDemonstrate\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eThe Deployment supports multi-camera input and high-speed interfaces for showcasing applications.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid #000; padding: 8px;\"\u003e\n\u003cul style=\"margin: 0; padding-left: 18px;\"\u003e\n\u003cli\u003eMIPI CSI-2\u003c\/li\u003e\n\u003cli\u003eIP-based input\u003c\/li\u003e\n\u003cli\u003eUSB 3.2\u003c\/li\u003e\n\u003cli\u003eReal-time vision AI demo via HDMI with minimal latency\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eAvailable Interfaces\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Gemini_Generated_Image_7t3n4p7t3n4p7t3n.png?v=1763376133\" alt=\"\"\u003e\u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 147.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 10.5938px;\"\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eNo.\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eInterfaces\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eHDMI 1.4 @ 4K\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e2\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e2 × MIPI CSI-2 Connectors\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e3\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eM.2 M — 4× PCIe Gen4 RC\/EP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e4\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e4× USB 3.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e5\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1× USB-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e6\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1× Gigabit Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e7\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eI²C \/ UART \/ GPIO \/ SPI \/ GPIO\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eResources\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eProduct Brief\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e\u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Modalix-SoM-Product-Brief_05.3.pdf?v=1770721342\" style=\"color: rgb(255, 42, 0);\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eWhat’s Included\u003cstrong\u003e\u003c\/strong\u003e\n\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 147.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 10.5938px;\"\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eParts\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eQuantity\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eModalix SoM 32GB \u003cspan style=\"color: rgb(255, 42, 0);\"\u003e(Commercial\/Industrial)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eCarrier Board\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eActive Heatsink\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eM.2 240GB NVME Solid State Drive\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e12V\/5A Power Supply\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eMetal Enclosure\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eVideos\u003c\/h2\u003e\n\u003cdiv style=\"position: relative; width: 100%; padding-top: 56.25%; background: #000;\"\u003e\u003cvideo preload=\"metadata\" playsinline=\"\" controls=\"controls\" style=\"position: absolute; top: 0; left: 0; width: 100%; height: 100%; object-fit: contain;\"\u003e\n    \u003csource type=\"video\/mp4\" src=\"https:\/\/cdn.shopify.com\/videos\/c\/o\/v\/82949aeb6dc7480ba08a1f4e08efa396.mp4\"\u003e\n    Your browser does not support the video tag.\n  \u003c\/source\u003e\u003c\/video\u003e\u003c\/div\u003e","brand":"SiMa.ai","offers":[{"title":"Commercial","offer_id":51369869181245,"sku":"SBC1158","price":84999.99,"currency_code":"INR","in_stock":true},{"title":"Industrial","offer_id":51369869214013,"sku":"SBC1159","price":89999.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/devkit-3-0_480x256_a69c6869-5027-45f2-92e6-1c0f93dfd6d4.webp?v=1774510820"},{"product_id":"thinkrobotics-nvidia-jetson-orin-nx-nano-edge-ai-5g-development-kit","title":"ThinkRobotics NVIDIA Jetson Orin NX \/ Nano Edge AI 5G Deployment Kit","description":"\u003ch2 style=\"text-align: center;\"\u003eThinkRobotics NVIDIA Jetson Orin NX \/ Nano Edge AI 5G Deployment Kit\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cmeta charset=\"utf-8\"\u003e\u003cspan\u003eThe Jetson Orin 5G AI Deployment Kit combines the powerful NVIDIA Jetson Orin™ NX \u003c\/span\u003e\u003cspan\u003eOrin™ Nano module with the versatile A608 carrier board and the high-performance RM520N-GL 5G module. This platform is designed for advanced edge AI applications requiring ultra-low latency connectivity, making it ideal for robotics, autonomous systems, UAVs, industrial automation, and next-generation AIoT deployments.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/ChatGPT_Image_Mar_10_2026_04_52_30_PM.png?v=1773143339\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003e\u003cspan\u003eFeature\u003c\/span\u003e\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eHigh-Performance Edge AI Platform\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eBuilt on NVIDIA Jetson Orin™ NX \/ Orin™ Nano modules delivering powerful GPU-accelerated computing for computer vision, robotics, AI inference, and generative AI workloads.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eIntegrated 5G Connectivity\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eEquipped with the RM520N-GL 5G module based on Qualcomm Snapdragon X62 platform supporting 5G SA and NSA networking for ultra-fast wireless communication.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eMulti-Mode Global Network Support\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eCompatible with 5G, LTE, and WCDMA networks with support for multiple global frequency bands ensuring reliable connectivity across regions.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eHigh-Speed USB 3.1 Interface\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eProvides high-bandwidth USB connectivity between the Jetson system and the 5G modem for ultra-low latency networking and high-speed data transfer.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDual Gigabit Ethernet\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eTwo onboard Gigabit Ethernet ports allow high-speed wired networking for industrial deployments and AI edge servers.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eFlexible Wireless Expansion\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eM.2 KEY B slot enables integration of 4G\/5G modules while M.2 KEY E supports WiFi expansion, providing flexible connectivity options.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eQuad Antenna Design\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eFour SMA antenna connectors ensure strong signal reception and stable high-speed wireless communication.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eMulti-Constellation GNSS Positioning\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eSupports GPS, GLONASS, Beidou, Galileo, and QZSS for high-precision positioning and navigation applications.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eRich IO for Robotics and Embedded Systems\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eIncludes CAN, I2C, SPI, UART, CSI camera interfaces, and multiple GPIOs for easy integration with sensors, cameras, and robotic subsystems.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eWide Power Input Range\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eOperates from 9V to 20V DC with up to 60W power input, making it suitable for mobile robots, drones, and industrial environments.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe Jetson Orin 5G Deployment Kit is designed to deliver powerful AI computing combined with next-generation wireless connectivity. By integrating NVIDIA's edge AI platform with the RM520N-GL 5G modem, the system enables real-time cloud connectivity, remote AI processing, and high-speed data streaming for intelligent edge applications.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe A608 carrier board provides a wide range of interfaces including dual Gigabit Ethernet, USB 3.2, CSI camera ports, CAN bus, and multiple expansion connectors, making it an ideal development platform for autonomous robots, AI surveillance systems, drones, and smart industrial devices.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eWith multi-constellation GNSS positioning and ultra-fast 5G connectivity, this platform is perfectly suited for applications requiring real-time telemetry, remote monitoring, edge analytics, and AI-powered automation.\u003c\/p\u003e\n\u003cp\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/RM520N-GL-5G-for-Jetson-Orin-details-5.jpg?v=1764744465\" style=\"display: block; margin-left: auto; margin-right: auto;\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e* Note: The frequency band diagram above is for reference only,\u003c\/span\u003e\u003cbr\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eplease confirm the supported bands according to your local service provider.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eApplication\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eAutonomous Robots\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eIndustrial AI \u0026amp; Automation\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eUnmanned Aerial Vehicles (UAVs)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eEdge AI Video Analytics\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eSmart Cities \u0026amp; Intelligent Transportation\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eRemote Monitoring Systems\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eAIoT Devices\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eAutonomous Marine Vehicles\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003e\n\u003cspan\u003eHardware\u003c\/span\u003e\u003cspan\u003e Ove\u003c\/span\u003e\u003cspan\u003erview\u003c\/span\u003e\n\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https:\/\/wdcdn.qpic.cn\/MTY4ODg1NzYyODMwNDA5OQ_556368_QFm3ICqR518LlQ4X_1705633232?w=1920\u0026amp;h=1080\u0026amp;type=image\/jpeg\"\u003e\u003cimg src=\"https:\/\/wdcdn.qpic.cn\/MTY4ODg1NzYyODMwNDA5OQ_800168_h1JqANomPobxe5Db_1705633237?w=1920\u0026amp;h=1080\u0026amp;type=image\/jpeg\"\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003e\u003cimg\u003e\u003cimg\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eSpecifications\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 274.313px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eProduct Name\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003eJetson Orin 5G AI Deployment Kit\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eAI Module Compatibility\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003eNVIDIA Jetson Orin™ NX \/ Orin™ Nano\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eCarrier Board\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003eA608 Jetson Carrier Board\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003e5G Module\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003eRM520N-GL (Qualcomm Snapdragon X62 Platform)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003e5G Network\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003e5G SA \/ NSA\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eNetworking\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003e2 × Gigabit Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eUSB\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003e4 × USB 3.2 Type-A, 1 × USB Type-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eCamera\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003e2 × 4-lane MIPI CSI\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eWireless\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003e5G via M.2 KEY B, WiFi via M.2 KEY E\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003eM.2 KEY M NVMe SSD Support\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eGNSS\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003eGPS \/ GLONASS \/ Beidou \/ Galileo \/ QZSS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003ePower Input\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003e9V – 20V DC (Max 60W)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 50.1664%;\"\u003e\u003cstrong\u003eOperating Temperature\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px; width: 49.8336%;\"\u003e-25°C to +65°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; text-align: center; width: 50.1664%;\"\u003e\u003cstrong\u003eAntenna Connectors\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; text-align: center; width: 49.8336%;\"\u003e4 × SMA\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePart List\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 156.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cstrong\u003e\u003cspan\u003eA608 Carrier Board for Jetson Orin™ NX \/ Orin™ Nano\u003c\/span\u003e\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cstrong\u003e\u003cspan\u003eJetson Orin NX \/ Orin Nano Module \u003cspan style=\"color: rgb(255, 42, 0);\"\u003eOPTIONS\u003c\/span\u003e\u003c\/span\u003e\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cb\u003eCooling Fan \/ Heatsink\u003c\/b\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cstrong\u003e\u003cspan\u003e240GB NVMe SSD\u003c\/span\u003e\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cstrong\u003e\u003cspan\u003eRM520N-GL 5G Module\u003c\/span\u003e\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cstrong\u003e\u003cspan\u003e5G Antennas\u003c\/span\u003e\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex4\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cstrong\u003ePower Supply\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; height: 19.5938px; width: 50.3375%; text-align: center;\"\u003e\u003cstrong\u003e\u003cspan\u003eAluminium Case \/ Enclosure\u003c\/span\u003e\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding-top: 8px; padding-right: 8px; padding-bottom: 8px; height: 19.5938px; text-align: center; width: 49.6625%;\"\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"NVIDIA","offers":[{"title":"with Orin Nano 8GB","offer_id":51478529900861,"sku":"SBC1080-1","price":126249.99,"currency_code":"INR","in_stock":true},{"title":"with Orin NX 8GB","offer_id":51478529966397,"sku":"SBC1080-2","price":159299.99,"currency_code":"INR","in_stock":true},{"title":"with Orin NX 16GB","offer_id":51478530031933,"sku":"SBC1080-3","price":199549.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/5G-IOT-Hub-6.png?v=1773143508"},{"product_id":"recomputer-robotics-j4012-with-gmsl-extension-intelligent-edge-ai-computer-with-nvidia-jetson-orin-nx-super-16gb","title":"reComputer Robotics J4012 with GMSL Extension - Intelligent Edge AI Computer with NVIDIA Jetson Orin NX Super 16GB","description":"\u003ch2 style=\"text-align: center;\"\u003ereComputer Robotics J4012 with NVIDIA Jetson Orin NX Super 16GB\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe reComputer Robotics J4012 with GMSL Extension is a compact, high-performance edge AI box designed for advanced robotics development. Compatible with NVIDIA® Jetson™ Orin™ NX modules in Super\/MAXN mode, it delivers up to 157 TOPS of AI performance, leveraging up to 1.7x improvement over its predecessor. Pre-installed with JetPack 6.2 and Linux BSP, it ensures seamless deployment, serving as a powerful robotic brain capable of processing complex data from various sensors, including GMSL cameras.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eFeatures\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 156.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 18.2007%; height: 39.1875px;\"\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 80.6385%; height: 39.1875px;\"\u003eUp to 157 TOPS using NVIDIA® Jetson™ Orin™ NX 16GB in Super\/MAXN mode\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 18.2007%; height: 19.5938px;\"\u003e\u003cstrong\u003eInterfaces\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 80.6385%; height: 19.5938px;\"\u003eDual RJ45, M.2 for 5G\/Wi-Fi\/BT, 6x USB 3.2, 2x CAN, GMSL2, I2C, UART\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 18.2007%; height: 39.1875px;\"\u003e\u003cstrong\u003ePower \u0026amp; Thermal\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 80.6385%; height: 39.1875px;\"\u003eOperates from -20°C to 60°C at 25W, up to 55°C in MAXN mode, supports 19–54V DC input\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 18.2007%; height: 39.1875px;\"\u003e\u003cstrong\u003eSoftware\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 80.6385%; height: 39.1875px;\"\u003ePre-installed JetPack 6.2 with Linux BSP, supports NVIDIA Isaac Sim for robotics applications\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 18.2007%; height: 19.5938px;\"\u003e\u003cstrong\u003eGMSL Support\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 80.6385%; height: 19.5938px;\"\u003eReady-to-use GMSL extension supporting multiple GMSL cameras in JetPack\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/image-robotic-J4012.webp?v=1777289136\" alt=\"\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eJetson Modules Performance with Super Mode\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 58.7814px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 24.0206%; height: 19.5938px;\"\u003e\u003cstrong\u003ePower Management\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 74.8186%; height: 19.5938px;\"\u003eEnhanced power management for improved efficiency and stability\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 24.0206%; height: 19.5938px;\"\u003e\u003cstrong\u003eFrame Processing\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 74.8186%; height: 19.5938px;\"\u003eImproved higher frame rate processing for smoother performance\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 24.0206%; height: 19.5938px;\"\u003e\u003cstrong\u003eInference\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 74.8186%; height: 19.5938px;\"\u003eReduced inference time for faster AI computations\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"626\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-J4011-2.png\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eSpecification\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 352.688px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 100%; height: 19.5938px;\" colspan=\"2\"\u003e\u003cstrong\u003eModule\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 39.1875px;\"\u003e\u003cstrong\u003eApplications Processor (AP)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 39.1875px;\"\u003eNVIDIA Jetson Orin™ NX 16GB\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e157 TOPS (MAXN)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e1024-core NVIDIA Ampere GPU with 32 Tensor Cores\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eGPU Max Frequency\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e1173 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e8-core Arm® Cortex-A78AE v8.2 64-bit, 2MB L2 + 4MB L3\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eCPU Max Frequency\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e2.0 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eDL Accelerator\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e2 × NVDLA v2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eDL Max Frequency\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e1.23 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eVision Accelerator\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e1 × PVA v2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e16GB LPDDR5, 128-bit, 102.4GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003ePower Modes\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e10W \/ 15W \/ 25W \/ 40W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eVideo Encode\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e1×4K60, 3×4K30, 6×1080p60, 12×1080p30 (H.265)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eVideo Decode\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e1×8K30, 2×4K60, 4×4K30, 9×1080p60, 18×1080p30 (H.265)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 39.1875px;\"\u003e\u003cstrong\u003eCSI Camera\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 39.1875px;\"\u003eUp to 4 cameras (8 via virtual channels), 8 lanes MIPI CSI-2, D-PHY 2.1 (up to 20Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 25.5814%; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eMechanical\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 74.4186%; text-align: center; height: 19.5938px;\"\u003e69.6mm × 45mm, 260-pin SO-DIMM connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 685.782px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd colspan=\"3\" style=\"border: 1px solid; text-align: center; height: 19.5938px; width: 100.166%;\"\u003e\u003cb\u003eCarrier Board\u003c\/b\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 75.9136%;\"\u003e1x M.2 KEY M PCIe\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd rowspan=\"3\" style=\"border: 1px solid; height: 58.7814px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eNetworking\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eM.2 KEY E\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003e1x M.2 Key E for WiFi\/Bluetooth module\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eM.2 KEY B\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003e1x M.2 Key B for 5G module\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eEthernet\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003e2x RJ-45 Gigabit Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.375px;\"\u003e\n\u003ctd rowspan=\"9\" style=\"border: 1px solid; height: 372.281px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eI\/O\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 78.375px; text-align: center; width: 23.588%;\"\u003eUSB\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 78.375px; text-align: center; width: 52.3256%;\"\u003e6x USB 3.2 Type-A (5Gbps)\u003cbr\u003e1x USB 3.0 Type-C (Host\/DP 1.4)\u003cbr\u003e1x USB 2.0 Type-C (Device Mode Only for Reflash\/Debug)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 23.588%;\"\u003eCAN\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 52.3256%;\"\u003e2x CAN0 (XT30(2+2))\u003cbr\u003e3x CAN1 (4-Pin GH-1.25 Header)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eDisplay\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003e1x DP1.4 (Type C Host)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eUART\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003e1x UART 4-Pin GH-1.25 Header\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eI2C\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003e2x I2C 4-Pin GH-1.25 Header\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 23.588%;\"\u003eFan\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 52.3256%;\"\u003e1x 4-Pin Fan Connector (5V PWM)\u003cbr\u003e1x 4-Pin Fan Connector (12V PWM)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 23.588%;\"\u003eExtension Port\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 52.3256%;\"\u003e1x Camera Expansion Header (GMSL2 board included)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 23.588%;\"\u003eRTC\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 52.3256%;\"\u003e1x RTC 2-pin\u003cbr\u003e1x RTC Socket\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 78.375px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 78.375px; text-align: center; width: 23.588%;\"\u003eLED \/ Buttons\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 78.375px; text-align: center; width: 52.3256%;\"\u003e3x LED (PWR, ACT, User)\u003cbr\u003ePinhole: 1x PWR, 1x RESET\u003cbr\u003eDIP: 1x REC\u003cbr\u003e5x Antenna Hole\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003ePower\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 75.9136%;\"\u003e19–54V XT30(2+2) (XT30 to 5525 DC Jack Cable included)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eJetpack Version\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 75.9136%;\"\u003eJetPack 6.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd rowspan=\"3\" style=\"border: 1px solid; height: 78.3751px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eMechanical\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 23.588%;\"\u003eDimensions (W × D × H)\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 39.1875px; text-align: center; width: 52.3256%;\"\u003e115mm × 115mm × 38mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eWeight\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003e200g\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 23.588%;\"\u003eInstallation\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 52.3256%;\"\u003eDesk, Wall-mounting\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 58.7812px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 58.7812px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eOperating Temperature\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid; height: 58.7812px; text-align: center; width: 75.9136%;\"\u003e-20°C ~ 60°C (25W Mode)\u003cbr\u003e-20°C ~ 55°C (MAXN Mode)\u003cbr\u003e(with reComputer Robotics heat sink with fan)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eWarranty\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 75.9136%;\"\u003e2 Years\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 24.2525%;\"\u003e\u003cstrong\u003eCertification\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid; height: 19.5938px; text-align: center; width: 75.9136%;\"\u003eRoHS, CE, FCC, KC (Pending)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 137.157px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\" colspan=\"3\"\u003e\u003cstrong\u003eCameras Supported in Jetpack\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e\u003cb\u003eManufacturer\u003c\/b\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e\u003cb\u003eModel\u003c\/b\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e\u003cb\u003eResolution\u003c\/b\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 78.3752px;\" rowspan=\"4\"\u003e\u003cstrong\u003eSensing\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003eSG3S-ISX031C-GMSL2F\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e1920H × 1536V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003eSG2-AR0233C-5200-G2A\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e1920H × 1080V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003eSG2-IMX390C-5200-G2A\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e1920H × 1080V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003eSG8S-AR0820C-5300-G2A\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e3840H × 2160V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e\u003cstrong\u003eOrbbec\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003eOrbbec Gemini 335LG\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; height: 19.5938px;\"\u003e3D\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eHardware Overview\u003cbr\u003e\n\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"900\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-114110308_1.jpeg\"\u003e\u003cimg height=\"1200\" width=\"1599\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-robotic-2.jpeg\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eApplication\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eHumanoid Robot \u0026amp; Manipulation\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eServing as a powerful brain for humanoid robots, the reComputer Robotics series delivers rich perception with precise motion control. Emulating human-like sensing, dexterity, mobility and whole-body coordination—seamlessly collaborating with people to get tasks done.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"447\" width=\"854\" src=\"https:\/\/wdcdn.qpic.cn\/MTY4ODg1NzU3ODgyNzc3Mw_403542_ZBsIfYDwP6YrlbL9_1765331085?w=2500\u0026amp;h=1308\u0026amp;type=image\/jpeg\" id=\"53dd74c9\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eAutonomous Robots, AMRs\/ AGVs\/ Logistics Robots\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe CAN bus links servos or motors to drive Robotic Arms and Autonomous Robots with millisecond-level joint coordination.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eLogistics Robots map in seconds via UART LiDAR, dodge on the fly and shuttle racks nonstop.\u003cbr\u003eI²C weaves temperature, humidity, IMU and fuel-gauge data into a net, giving robots early-maintenance alerts.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eUSB cameras scan barcodes while on the move, and a USB ticket printer labels parcels in real time—zero manual labor from inbound to outbound.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eDual-RJ45 link-aggregation delivers video to the Edge AI reCopmputer in \u0026lt;1 ms for real-time QC and remote monitoring.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"470\" width=\"837\" src=\"https:\/\/wdcdn.qpic.cn\/MTY4ODg1NzU3ODgyNzc3Mw_456274_LaWWTRiTvkiCZB4I_1765331122?w=4800\u0026amp;h=2700\u0026amp;type=image\/jpeg\" id=\"a7dc60c2\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eHigh-Performance Vision for Robotics\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eCombining a GMSL 2 camera with a reComputer Robotics enables advanced vision-based robotics. Sensing 3MP GMSL 2 camera supports real-time object detection, panoramic environment awareness, and multi-camera 3D reconstruction . The high-bandwidth, low-latency GMSL 2 link supports long cable runs and multi-camera setups, while the Jetson Orin NX delivers real-time AI processing for perception, mapping, and control.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"637\" width=\"1740\" src=\"https:\/\/files.seeedstudio.com\/wiki\/reComputer-Jetson\/J501\/yolo_1.gif\" id=\"210c380a\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003e3D Vision and GMSL 2 Connectivity for Robotics\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe reComputer Robotics GMSL Extension supports the Orbbec Gemini 335LG Stereo Vision 3D Camera, providing accurate real-time 3D perception for advanced robotics. With the MAX96712 deserializer and mini-FAKRA connector, it ensures secure, low-latency, and reliable data transmission, ideal for AMRs, robotic arms, and collaborative robots. Precise depth sensing enables smarter navigation, robust object recognition, and reliable obstacle avoidance across mobile robots, delivery systems, and shelf-stocking applications.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"625\" width=\"857\" src=\"https:\/\/wdcdn.qpic.cn\/MTY4ODg1NTkyNTI4NTI1NA_409825__MXGaqzpcOJ4xIrg_1765250958?w=1878\u0026amp;h=1368\u0026amp;type=image\/png\" id=\"a44e43e0\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eDocuments\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 235.125px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eUser Manual \u0026amp; Datasheet\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/reComputer_robotics_J401_user_manual.pdf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eCarrier Board Schematic\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/reComputer%20Robotics%20J401_V1.0_SCH_250421.pdf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003ePower Board Schematic\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/Power%20board%20for%20reComputer%20Robotics_V1.0_SCH_250507.pdf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eGMSL Board Schematic\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/GMSL%20board%20for%20reComputer%20Robotics_V1.0_SCH_250717.pdf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003e3D File\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/recomputer_robotics_j401.stp\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 39.1875px; text-align: center;\"\u003eMechanical Document-reComputer Robotics PCBA\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 39.1875px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/Mechanical_reComputer_Robotics_PCBA.dxf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eSeeed NVIDIA Jetson Product Catalog\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/wiki\/Seeed_Jetson\/Seeed_NVIDIA_Jetson_Catalog_in_Robotics_and_Edge_AI.pdf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eNvidia Jetson Comparison\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/nvidia-jetson-comparison-nano-tx2-nx-xavier-nx-agx-orin\/\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eSeeed Nvidia Jetson Success Cases\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2023\/07\/Seeed_NVIDIA_Jetson_Success_Cases_and_Examples.pdf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eSeeed Jetson One Pager\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/files.seeedstudio.com\/wiki\/Seeed_Jetson\/Seeed-Jetson-one-pager.pdf\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 50.1664%; height: 19.5938px; text-align: center;\"\u003eFlash BSP for Jetson\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.8336%; height: 19.5938px; text-align: center;\"\u003e\u003ca href=\"https:\/\/wiki.seeedstudio.com\/flash\/jetpack_to_selected_product\/\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePart List\u003cbr\u003e\n\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 156.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 50.4967%; text-align: center;\"\u003e\u003cb\u003eItems\u003c\/b\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 49.5033%; text-align: center;\"\u003e\u003cb\u003eQuantity\u003c\/b\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 50.4967%; text-align: center;\"\u003eJetson Orin™ NX 16GB module\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 49.5033%; text-align: center;\"\u003ex 1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 50.4967%; text-align: center;\"\u003eSeeed Carrier Board (reComputer Robotics J401) with GMSL Extension\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 49.5033%; text-align: center;\"\u003ex 1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 50.4967%; text-align: center;\"\u003e128GB NVMe SSD\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 49.5033%; text-align: center;\"\u003ex 1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 50.4967%; text-align: center;\"\u003eAluminum Case and Heatsink with Fan\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 49.5033%; text-align: center;\"\u003ex 1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 50.4967%; text-align: center;\"\u003eUSB Cable (Type-A to Type-C)\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; height: 19.5938px; width: 49.5033%; 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It supports a wide range of operating temperature from -20℃ to 65℃. Built for fast development and production, it features Wi-Fi\/BT\/LTE wireless communication capability and Ethernet, ensuring seamless integration, ideal for video analysis, multimodal perception, and robotics.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003ciframe title=\"reComputer Super for NVIDIA Jetson Orin NX\/Orin Nano, supportting Super\/MAXN Mode\" src=\"https:\/\/www.youtube.com\/embed\/brhkUmWFnAM\" height=\"539\" width=\"943\"\u003e\u003c\/iframe\u003e\u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 195.938px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 21.1386%; height: 39.1875px;\"\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 77.644%; height: 39.1875px;\"\u003eDelivers up to 117 TOPS in MAXN Super Mode, ideal for vision AI, robotics, and generative AI applications\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 21.1386%; height: 39.1875px;\"\u003e\u003cstrong\u003ePower Modes\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 77.644%; height: 39.1875px;\"\u003eConfigurable power modes from 10W to 40W for optimized performance and efficiency\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 21.1386%; height: 39.1875px;\"\u003e\u003cstrong\u003eThermal Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 77.644%; height: 39.1875px;\"\u003eOperates from -20°C to 60°C at 40W, and up to 65°C at 25W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 21.1386%; height: 39.1875px;\"\u003e\u003cstrong\u003eInterfaces\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 77.644%; height: 39.1875px;\"\u003e2x RJ45, SIM card slot, 4x USB 3.2, HDMI 2.1, CAN, M.2 Key E\/M, Mini-PCIe, 4x CSI\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 39.1875px;\"\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 21.1386%; height: 39.1875px;\"\u003e\u003cstrong\u003eSoftware \u0026amp; Storage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 77.644%; height: 39.1875px;\"\u003ePre-installed JetPack 6.2 with 128GB NVMe SSD, supports NVIDIA Isaac, Hugging Face, ROS2\/ROS1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/reComputer_Super_J4011_4x_25892074-9f62-4ec7-86ef-460e3eeca84b.webp?v=1777095777\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"626\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-J4011-2.png\"\u003e\u003cimg alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/111-photo\/image_3.png\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eHardware Overview\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"900\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-_J4011-3.jpeg\"\u003e\u003cimg height=\"800\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-_J401-4.jpeg\"\u003e\u003cimg height=\"800\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-_J4011-5.jpeg\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eApplication\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe NVIDIA AI software stack is designed for accelerate AI application and deployment:\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"789\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-_J4011-6.png\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eDesigned for Edge AI Computer Vision Applications\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eJetson Platform Services provide a platform to simplify development, deployment and management of Edge AI applications on NVIDIA Jetson like BEV sensing demo with 4 USB cameras.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"492\" width=\"1200\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image-_J401-7.png\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eDesigned for demanding AI application\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eSuch as AMR, smart retail, industrial automation, and video surveillance, smart video analysis scenario\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg height=\"803\" width=\"843\" alt=\"\" src=\"https:\/\/media-cdn.seeedstudio.com\/media\/wysiwyg\/upload\/image6.png\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eWe have Jetson-example prepared for you! It offers one-line deploy projects edge AI applications of generative AI including Ollama, Llama3; computer vision including YOLOv8, and others. We have configured all environment for you to provides single command deployment of projects. \u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eDocuments\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 176.344px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eUser Manual \u0026amp; Datasheet\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/reComputer_super_user_manual.pdf\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eTemperature Test Report\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/reComputer_Super_Temperature_Test_Report.pdf\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eSchematic\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/reComputer%20Super%20J401_v1.0_SCH_PDF_250401.pdf\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003e3D File\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/reComputer%20Super%20J401.stp\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eMechanical Document-reComputer Super\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/Mechanical_reComputer_Super.dxf\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eMechanical Document-reComputer Super PCBA\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/files.seeedstudio.com\/products\/NVIDIA-Jetson\/Mechanical_reComputer_Super_PCBA.dxf\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eSeeed Nvidia Jetson Success Cases\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2023\/07\/Seeed_NVIDIA_Jetson_Success_Cases_and_Examples.pdf\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eSeeed Jetson One Pager\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/files.seeedstudio.com\/wiki\/Seeed_Jetson\/Seeed-Jetson-one-pager.pdf\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: left;\"\u003eFlash BSP for Jetson\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; width: 49.4196%; height: 19.5938px; text-align: center;\"\u003e\u003ca rel=\"noopener\" href=\"https:\/\/wiki.seeedstudio.com\/flash\/jetpack_to_selected_product\/\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePart List\u003cbr\u003e\n\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 118.156px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 19.6875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.9118%; height: 19.6875px; text-align: left;\"\u003eJetson Orin™ NX 16GB \/ NX 8GB \/ Nano 8GB \/ Nano 4GB Module\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 50.0882%; height: 19.6875px;\"\u003e 1 \u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.6875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.9118%; height: 19.6875px; text-align: left;\"\u003eSeeed Carrier Board (reComputer Super J401)\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 50.0882%; height: 19.6875px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.6875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.9118%; height: 19.6875px; text-align: left;\"\u003e128GB NVMe SSD\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 50.0882%; height: 19.6875px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.6875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.9118%; height: 19.6875px; text-align: left;\"\u003eAluminum Case and Heatsink with Fan\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 50.0882%; height: 19.6875px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.6875px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.9118%; height: 19.6875px; text-align: left;\"\u003eUSB Cable (Type-A to Type-C)\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 50.0882%; height: 19.6875px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.7188px;\"\u003e\n\u003ctd style=\"border: 1px solid; width: 49.9118%; height: 19.7188px; text-align: left;\"\u003eUser Manual\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid; text-align: center; width: 50.0882%; height: 19.7188px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"Seeed Studio","offers":[{"title":"Default Title","offer_id":51637587607869,"sku":"SBC1150","price":173099.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/1-114110311-recomputer-super-j3010-8g_70fa5bec-ceb6-419a-9875-b9b3322f536c.jpg?v=1776946517"},{"product_id":"nvidia-jetson-orin-super-nano-deployment-kit-made-in-india-copy","title":"ThinkRobotics NVIDIA Jetson Orin NX \/ Nano Edge AI Deployment Kit","description":"\u003cstyle\u003e\n\/* =========================================================\n   THINKROBOTICS JETSON DESCRIPTION\n   LIGHT \/ DARK MODE SAFE CSS\n   CONTENT + ALIGNMENT + SPACING PRESERVED\n   ========================================================= *\/\n\n.tr-jetson {\n  max-width: 1200px;\n  margin: 0 auto;\n  font-family: Arial, Helvetica, sans-serif;\n  line-height: 1.6;\n\n  \/* Use Shopify theme colors where available *\/\n  --tr-text: rgb(var(--color-foreground, 34, 34, 34));\n  --tr-heading: rgb(var(--color-foreground, 17, 17, 17));\n  --tr-bg: rgb(var(--color-background, 255, 255, 255));\n\n  --tr-card-bg: rgba(127, 127, 127, 0.05);\n  --tr-soft-bg: rgba(127, 127, 127, 0.07);\n  --tr-header-bg: rgba(127, 127, 127, 0.10);\n  --tr-border: rgba(127, 127, 127, 0.28);\n\n  --tr-accent: #c20001;\n}\n\n\/* ---------------------------------------------------------\n   GLOBAL CONTENT\n   --------------------------------------------------------- *\/\n\n.tr-jetson * {\n  box-sizing: border-box;\n}\n\n.tr-jetson,\n.tr-jetson p,\n.tr-jetson li,\n.tr-jetson td,\n.tr-jetson th {\n  color: var(--tr-text);\n}\n\n.tr-jetson h1,\n.tr-jetson h2,\n.tr-jetson h3,\n.tr-jetson h4,\n.tr-jetson h5,\n.tr-jetson h6,\n.tr-jetson strong,\n.tr-jetson b {\n  color: var(--tr-heading);\n}\n\n\n\/* ---------------------------------------------------------\n   HERO\n   --------------------------------------------------------- *\/\n\n.tr-hero {\n  background: var(--tr-soft-bg);\n  border-radius: 18px;\n  padding: 45px 30px;\n  text-align: center;\n  margin-bottom: 35px;\n}\n\n.tr-hero h1 {\n  font-size: 34px;\n  line-height: 1.25;\n  margin: 0 0 15px;\n  font-weight: 700;\n  color: var(--tr-heading);\n}\n\n.tr-hero .tr-subtitle {\n  font-size: 19px;\n  color: var(--tr-text);\n  max-width: 850px;\n  margin: 0 auto 22px;\n  opacity: 0.78;\n}\n\n\n\/* ---------------------------------------------------------\n   BADGES\n   --------------------------------------------------------- *\/\n\n.tr-badges {\n  display: flex;\n  justify-content: center;\n  flex-wrap: wrap;\n  gap: 10px;\n  margin-top: 20px;\n}\n\n.tr-badge {\n  background: var(--tr-heading);\n  color: var(--tr-bg);\n  padding: 8px 15px;\n  border-radius: 30px;\n  font-size: 14px;\n  font-weight: 600;\n}\n\n\n\/* ---------------------------------------------------------\n   WARNING\n   --------------------------------------------------------- *\/\n\n.tr-warning {\n  background: rgba(194, 0, 1, 0.08);\n  border: 1px solid rgba(194, 0, 1, 0.35);\n  color: #c20001;\n  padding: 14px 18px;\n  border-radius: 10px;\n  margin: 25px auto 0;\n  max-width: 850px;\n  font-size: 14px;\n  font-weight: 600;\n}\n\n.tr-warning strong,\n.tr-warning b {\n  color: #c20001;\n}\n\n\n\/* ---------------------------------------------------------\n   SECTIONS\n   --------------------------------------------------------- *\/\n\n.tr-section {\n  margin: 45px 0;\n}\n\n.tr-section h2 {\n  font-size: 27px;\n  text-align: center;\n  margin-bottom: 12px;\n  color: var(--tr-heading);\n}\n\n.tr-section-intro {\n  text-align: center;\n  max-width: 850px;\n  margin: 0 auto 28px;\n  color: var(--tr-text);\n  opacity: 0.78;\n  font-size: 16px;\n}\n\n\n\/* ---------------------------------------------------------\n   IMAGES\n   --------------------------------------------------------- *\/\n\n.tr-image {\n  text-align: center;\n  margin: 25px 0;\n}\n\n.tr-image img {\n  max-width: 100%;\n  height: auto;\n  border-radius: 14px;\n}\n\n\n\/* ---------------------------------------------------------\n   VARIANTS\n   --------------------------------------------------------- *\/\n\n.tr-variants {\n  display: grid;\n  grid-template-columns: repeat(4, 1fr);\n  gap: 16px;\n  margin-top: 25px;\n}\n\n.tr-variant {\n  border: 1px solid var(--tr-border);\n  border-radius: 14px;\n  padding: 22px 15px;\n  text-align: center;\n  background: var(--tr-card-bg);\n  color: var(--tr-text);\n  transition: 0.2s ease;\n}\n\n.tr-variant:hover {\n  box-shadow: 0 8px 25px rgba(0,0,0,0.08);\n  transform: translateY(-2px);\n}\n\n.tr-variant h3 {\n  margin: 0 0 8px;\n  font-size: 18px;\n  color: var(--tr-heading);\n}\n\n.tr-variant .memory {\n  font-size: 25px;\n  font-weight: 700;\n  color: var(--tr-accent);\n}\n\n.tr-variant p {\n  margin: 7px 0 0;\n  color: var(--tr-text);\n  opacity: 0.70;\n  font-size: 14px;\n}\n\n\n\/* ---------------------------------------------------------\n   FEATURE CARDS\n   --------------------------------------------------------- *\/\n\n.tr-features {\n  display: grid;\n  grid-template-columns: repeat(3, 1fr);\n  gap: 18px;\n}\n\n.tr-feature {\n  border: 1px solid var(--tr-border);\n  border-radius: 14px;\n  padding: 24px;\n  background: var(--tr-card-bg);\n  color: var(--tr-text);\n}\n\n.tr-feature h3 {\n  margin: 0 0 9px;\n  font-size: 18px;\n  color: var(--tr-heading);\n}\n\n.tr-feature p {\n  margin: 0;\n  color: var(--tr-text);\n  opacity: 0.75;\n  font-size: 14px;\n}\n\n\n\/* ---------------------------------------------------------\n   INDUSTRIAL HIGHLIGHT\n   --------------------------------------------------------- *\/\n\n.tr-highlight {\n  background: var(--tr-heading);\n  color: var(--tr-bg);\n  border-radius: 16px;\n  padding: 35px 28px;\n  margin: 40px 0;\n}\n\n.tr-highlight h2,\n.tr-highlight p,\n.tr-highlight strong,\n.tr-highlight b,\n.tr-highlight li,\n.tr-highlight span {\n  color: var(--tr-bg);\n}\n\n.tr-highlight h2 {\n  text-align: left;\n  margin-top: 0;\n}\n\n.tr-highlight ul {\n  margin: 15px 0 0;\n  padding-left: 22px;\n}\n\n.tr-highlight li {\n  margin-bottom: 8px;\n}\n\n\n\/* ---------------------------------------------------------\n   TABLES\n   --------------------------------------------------------- *\/\n\n.tr-table-wrap {\n  overflow-x: auto;\n  margin-top: 20px;\n}\n\n.tr-table {\n  width: 100%;\n  border-collapse: collapse;\n  min-width: 700px;\n  font-size: 14px;\n  color: var(--tr-text);\n  background: transparent;\n}\n\n.tr-table th,\n.tr-table td {\n  border: 1px solid var(--tr-border);\n  padding: 13px 14px;\n  text-align: left;\n  vertical-align: top;\n  color: var(--tr-text);\n  background: transparent;\n}\n\n.tr-table th {\n  background: var(--tr-header-bg);\n  font-weight: 700;\n  color: var(--tr-heading);\n}\n\n\/*\n   IMPORTANT:\n   Do NOT use white\/gray fixed backgrounds here.\n   This keeps all table rows compatible with both themes.\n*\/\n\n.tr-table tr:nth-child(even) td,\n.tr-table tr:nth-child(odd) td {\n  background: transparent;\n  color: var(--tr-text);\n}\n\n.tr-table td strong,\n.tr-table td b,\n.tr-table th strong,\n.tr-table th b {\n  color: var(--tr-heading);\n}\n\n\n\/* ---------------------------------------------------------\n   KIT BOXES\n   --------------------------------------------------------- *\/\n\n.tr-kit {\n  display: grid;\n  grid-template-columns: 1fr 1fr;\n  gap: 22px;\n}\n\n.tr-kit-box {\n  border: 1px solid var(--tr-border);\n  border-radius: 14px;\n  padding: 25px;\n  background: var(--tr-card-bg);\n  color: var(--tr-text);\n}\n\n.tr-kit-box h3 {\n  margin-top: 0;\n  font-size: 20px;\n  color: var(--tr-heading);\n}\n\n.tr-kit-box ul {\n  margin: 0;\n  padding-left: 20px;\n}\n\n.tr-kit-box li,\n.tr-kit-box p {\n  color: var(--tr-text);\n}\n\n\n\/* ---------------------------------------------------------\n   APPLICATIONS\n   --------------------------------------------------------- *\/\n\n.tr-applications {\n  display: grid;\n  grid-template-columns: repeat(4, 1fr);\n  gap: 15px;\n}\n\n.tr-application {\n  background: var(--tr-soft-bg);\n  border-radius: 13px;\n  padding: 20px;\n  text-align: center;\n  font-weight: 600;\n  color: var(--tr-heading);\n}\n\n.tr-application strong,\n.tr-application b {\n  color: var(--tr-heading);\n}\n\n\n\/* ---------------------------------------------------------\n   NOTE\n   --------------------------------------------------------- *\/\n\n.tr-note {\n  background: var(--tr-soft-bg);\n  border-left: 4px solid var(--tr-heading);\n  padding: 17px 20px;\n  margin-top: 25px;\n  font-size: 14px;\n  color: var(--tr-text);\n}\n\n.tr-note strong,\n.tr-note b {\n  color: var(--tr-heading);\n}\n\n\n\/* ---------------------------------------------------------\n   FOOTER\n   --------------------------------------------------------- *\/\n\n.tr-footer {\n  background: var(--tr-soft-bg);\n  border-radius: 15px;\n  padding: 28px;\n  text-align: center;\n  margin-top: 45px;\n  color: var(--tr-text);\n}\n\n.tr-footer h2 {\n  color: var(--tr-heading);\n}\n\n.tr-footer p {\n  color: var(--tr-text);\n}\n\n\n\/* =========================================================\n   DARK MODE\n   Supports common Shopify\/theme dark-mode class patterns\n   ========================================================= *\/\n\nhtml.dark .tr-jetson,\nbody.dark .tr-jetson,\nhtml.dark-mode .tr-jetson,\nbody.dark-mode .tr-jetson,\nhtml.theme-dark .tr-jetson,\nbody.theme-dark .tr-jetson,\nhtml[data-theme=\"dark\"] .tr-jetson,\nbody[data-theme=\"dark\"] .tr-jetson,\nhtml[data-theme=\"Dark\"] .tr-jetson,\nbody[data-theme=\"Dark\"] .tr-jetson {\n\n  --tr-text: #eeeeee;\n  --tr-heading: #ffffff;\n  --tr-bg: #111111;\n\n  --tr-card-bg: rgba(255,255,255,0.045);\n  --tr-soft-bg: rgba(255,255,255,0.065);\n  --tr-header-bg: rgba(255,255,255,0.09);\n  --tr-border: rgba(255,255,255,0.18);\n}\n\n\n\/* ---------------------------------------------------------\n   DARK MODE - TABLE\n   --------------------------------------------------------- *\/\n\nhtml.dark .tr-table,\nbody.dark .tr-table,\nhtml.dark-mode .tr-table,\nbody.dark-mode .tr-table,\nhtml.theme-dark .tr-table,\nbody.theme-dark .tr-table,\nhtml[data-theme=\"dark\"] .tr-table,\nbody[data-theme=\"dark\"] .tr-table,\nhtml[data-theme=\"Dark\"] .tr-table,\nbody[data-theme=\"Dark\"] .tr-table {\n\n  color: #eeeeee;\n  background: transparent;\n}\n\nhtml.dark .tr-table th,\nbody.dark .tr-table th,\nhtml.dark-mode .tr-table th,\nbody.dark-mode .tr-table th,\nhtml.theme-dark .tr-table th,\nbody.theme-dark .tr-table th,\nhtml[data-theme=\"dark\"] .tr-table th,\nbody[data-theme=\"dark\"] .tr-table th,\nhtml[data-theme=\"Dark\"] .tr-table th,\nbody[data-theme=\"Dark\"] .tr-table th {\n\n  color: #ffffff;\n  background: rgba(255,255,255,0.09);\n  border-color: rgba(255,255,255,0.18);\n}\n\nhtml.dark .tr-table td,\nbody.dark .tr-table td,\nhtml.dark-mode .tr-table td,\nbody.dark-mode .tr-table td,\nhtml.theme-dark .tr-table td,\nbody.theme-dark .tr-table td,\nhtml[data-theme=\"dark\"] .tr-table td,\nbody[data-theme=\"dark\"] .tr-table td,\nhtml[data-theme=\"Dark\"] .tr-table td,\nbody[data-theme=\"Dark\"] .tr-table td {\n\n  color: #eeeeee;\n  background: transparent;\n  border-color: rgba(255,255,255,0.18);\n}\n\nhtml.dark .tr-table td strong,\nbody.dark .tr-table td strong,\nhtml.dark-mode .tr-table td strong,\nbody.dark-mode .tr-table td strong,\nhtml.theme-dark .tr-table td strong,\nbody.theme-dark .tr-table td strong,\nhtml[data-theme=\"dark\"] .tr-table td strong,\nbody[data-theme=\"dark\"] .tr-table td strong {\n\n  color: #ffffff;\n}\n\n\n\/* ---------------------------------------------------------\n   DARK MODE - APPLICATIONS\n   --------------------------------------------------------- *\/\n\nhtml.dark .tr-application,\nbody.dark .tr-application,\nhtml.dark-mode .tr-application,\nbody.dark-mode .tr-application,\nhtml.theme-dark .tr-application,\nbody.theme-dark .tr-application,\nhtml[data-theme=\"dark\"] .tr-application,\nbody[data-theme=\"dark\"] .tr-application {\n\n  background: rgba(255,255,255,0.075);\n  color: #ffffff;\n}\n\nhtml.dark .tr-application strong,\nbody.dark .tr-application strong,\nhtml.dark-mode .tr-application strong,\nbody.dark-mode .tr-application strong,\nhtml.theme-dark .tr-application strong,\nbody.theme-dark .tr-application strong {\n\n  color: #ffffff;\n}\n\n\n\/* ---------------------------------------------------------\n   DARK MODE - CARDS\n   --------------------------------------------------------- *\/\n\nhtml.dark .tr-variant,\nbody.dark .tr-variant,\nhtml.dark-mode .tr-variant,\nbody.dark-mode .tr-variant,\nhtml.theme-dark .tr-variant,\nbody.theme-dark .tr-variant,\nhtml[data-theme=\"dark\"] .tr-variant,\nbody[data-theme=\"dark\"] .tr-variant,\nhtml.dark .tr-feature,\nbody.dark .tr-feature,\nhtml.dark-mode .tr-feature,\nbody.dark-mode .tr-feature,\nhtml.theme-dark .tr-feature,\nbody.theme-dark .tr-feature,\nhtml[data-theme=\"dark\"] .tr-feature,\nbody[data-theme=\"dark\"] .tr-feature,\nhtml.dark .tr-kit-box,\nbody.dark .tr-kit-box,\nhtml.dark-mode .tr-kit-box,\nbody.dark-mode .tr-kit-box,\nhtml.theme-dark .tr-kit-box,\nbody.theme-dark .tr-kit-box,\nhtml[data-theme=\"dark\"] .tr-kit-box,\nbody[data-theme=\"dark\"] .tr-kit-box {\n\n  background: rgba(255,255,255,0.045);\n  border-color: rgba(255,255,255,0.18);\n}\n\n\n\/* ---------------------------------------------------------\n   DARK MODE - NOTE \/ FOOTER \/ HERO\n   --------------------------------------------------------- *\/\n\nhtml.dark .tr-hero,\nbody.dark .tr-hero,\nhtml.dark-mode .tr-hero,\nbody.dark-mode .tr-hero,\nhtml.theme-dark .tr-hero,\nbody.theme-dark .tr-hero,\nhtml[data-theme=\"dark\"] .tr-hero,\nbody[data-theme=\"dark\"] .tr-hero,\nhtml.dark .tr-note,\nbody.dark .tr-note,\nhtml.dark-mode .tr-note,\nbody.dark-mode .tr-note,\nhtml.theme-dark .tr-note,\nbody.theme-dark .tr-note,\nhtml[data-theme=\"dark\"] .tr-note,\nbody[data-theme=\"dark\"] .tr-note,\nhtml.dark .tr-footer,\nbody.dark .tr-footer,\nhtml.dark-mode .tr-footer,\nbody.dark-mode .tr-footer,\nhtml.theme-dark .tr-footer,\nbody.theme-dark .tr-footer,\nhtml[data-theme=\"dark\"] .tr-footer,\nbody[data-theme=\"dark\"] .tr-footer {\n\n  background: rgba(255,255,255,0.05);\n}\n\n\n\/* =========================================================\n   MOBILE\n   ========================================================= *\/\n\n@media (max-width: 900px) {\n\n  .tr-variants {\n    grid-template-columns: repeat(2, 1fr);\n  }\n\n  .tr-features {\n    grid-template-columns: repeat(2, 1fr);\n  }\n\n  .tr-applications {\n    grid-template-columns: repeat(2, 1fr);\n  }\n\n}\n\n@media (max-width: 600px) {\n\n  .tr-hero {\n    padding: 30px 18px;\n  }\n\n  .tr-hero h1 {\n    font-size: 27px;\n  }\n\n  .tr-hero .tr-subtitle {\n    font-size: 16px;\n  }\n\n  .tr-variants,\n  .tr-features,\n  .tr-kit,\n  .tr-applications {\n    grid-template-columns: 1fr;\n  }\n\n  .tr-section h2 {\n    font-size: 23px;\n  }\n\n}\n\u003c\/style\u003e\n\u003cdiv class=\"tr-jetson\"\u003e\n\u003c!-- HERO --\u003e\n\u003csection class=\"tr-hero\"\u003e\n\u003ch1\u003eThinkRobotics NVIDIA Jetson Orin NX \/ Nano Edge AI Deployment Kit\u003c\/h1\u003e\n\u003cp class=\"tr-subtitle\"\u003eA ready-to-deploy Jetson-based AI computing platform combining NVIDIA Jetson modules, Waveshare carrier board, NVMe storage, wireless connectivity, industrial-grade metal enclosure and 12V power supply.\u003c\/p\u003e\n\u003cdiv class=\"tr-badges\"\u003e\n\u003cspan class=\"tr-badge\"\u003eJetson Orin Nano\u003c\/span\u003e \u003cspan class=\"tr-badge\"\u003eJetson Orin NX\u003c\/span\u003e \u003cspan class=\"tr-badge\"\u003eIndustrial Metal Case\u003c\/span\u003e \u003cspan class=\"tr-badge\"\u003eNVMe SSD\u003c\/span\u003e \u003cspan class=\"tr-badge\"\u003eWi-Fi + Bluetooth\u003c\/span\u003e \u003cspan class=\"tr-badge\"\u003e12V 5A Power Supply\u003c\/span\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c!-- PRODUCT OVERVIEW --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003ch2\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/WhatsAppImage2026-09-05at5.26.12PM.jpg?v=1788609426\" alt=\"\"\u003e\u003c\/h2\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003c\/section\u003e\n\u003c!-- VARIANTS --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003ch2\u003eChoose Your Jetson Configuration\u003c\/h2\u003e\n\u003cp class=\"tr-section-intro\"\u003eSelect the Jetson module based on your required AI performance, memory capacity and deployment requirements.\u003c\/p\u003e\n\u003cdiv class=\"tr-variants\"\u003e\n\u003cdiv class=\"tr-variant\"\u003e\n\u003cdiv class=\"memory\"\u003e4GB\u003c\/div\u003e\n\u003ch3\u003eJetson Orin Nano\u003c\/h3\u003e\n\u003cp\u003eEntry-level AI edge computing\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-variant\"\u003e\n\u003cdiv class=\"memory\"\u003e8GB\u003c\/div\u003e\n\u003ch3\u003eJetson Orin Nano\u003c\/h3\u003e\n\u003cp\u003eHigher-performance AI workloads\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-variant\"\u003e\n\u003cdiv class=\"memory\"\u003e8GB\u003c\/div\u003e\n\u003ch3\u003eJetson Orin NX\u003c\/h3\u003e\n\u003cp\u003eAdvanced AI and robotics\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-variant\"\u003e\n\u003cdiv class=\"memory\"\u003e16GB\u003c\/div\u003e\n\u003ch3\u003eJetson Orin NX\u003c\/h3\u003e\n\u003cp\u003eHigh-performance edge AI\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c!-- KEY FEATURES --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cdiv class=\"tr-features\"\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eNVIDIA Jetson Platform\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003eAvailable with Jetson Orin Nano 4GB\/8GB and Jetson Orin NX 8GB\/16GB module configurations.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eWaveshare Carrier Board\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003eReliable carrier platform providing interfaces for storage, networking, USB, GPIO and other peripheral connectivity.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eIndustrial Metal Enclosure\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003eRugged industrial-grade metal case designed to provide mechanical protection for the Jetson computing platform during deployment.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eNVMe SSD Storage\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003ePre-installed NVMe solid-state storage provides fast read\/write performance for operating systems, applications and AI workloads.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eWi-Fi + Bluetooth\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003eIntegrated wireless connectivity with Wi-Fi and Bluetooth support for networked edge applications and peripheral communication.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003e12V 5A Power Supply\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003eIncludes a 12V 5A power supply suitable for powering the assembled Jetson platform.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c!-- INDUSTRIAL CASE --\u003e\n\u003csection class=\"tr-highlight\"\u003e\n\u003ch2 style=\"text-align: center;\"\u003eBuilt for Industrial Deployment\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eUnlike an open development-board setup, this configuration is assembled inside an industrial-grade metal enclosure, making it more suitable for integration into robotics, automation and edge-computing systems.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eRigid metal construction | \u003cspan style=\"font-size: 0.875rem;\"\u003eProtection for the Jetson module and carrier board\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eImproved mechanical durability | Suitable for embedded and industrial installations\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eDesigned for long-term deployment environments\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/section\u003e\n\u003c!-- COMMON COMPONENTS --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003ch2\u003eCommon Components Across All Variants\u003c\/h2\u003e\n\u003cdiv class=\"tr-kit\"\u003e\n\u003cdiv class=\"tr-kit-box\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eIncluded Hardware\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003eSelected NVIDIA Jetson Orin Nano \/ Orin NX module\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eWaveshare carrier board\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eIndustrial-grade metal enclosure\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eNVMe SSD\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eWi-Fi + Bluetooth wireless module\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eAntennas\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eCooling solution\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-kit-box\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003ePower \u0026amp; Connectivity\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003e12V 5A power supply\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eGigabit Ethernet connectivity\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eUSB connectivity\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eGPIO \/ expansion interfaces\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eCSI camera interfaces supported by carrier board\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eWireless network connectivity\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c!-- SPECIFICATION --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eJetson Module Comparison\u003c\/h2\u003e\n\u003cdiv class=\"tr-table-wrap\"\u003e\n\u003ctable style=\"width: 100%; min-width: 1050px; border-collapse: collapse; font-size: 14px; line-height: 1.5;\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 14px; background: rgba(127, 127, 127, 0.1); text-align: center;\"\u003eSpecification\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 14px; background: rgba(127, 127, 127, 0.1); text-align: center;\"\u003eJetson Orin Nano 4GB\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 14px; background: rgba(127, 127, 127, 0.1); text-align: center;\"\u003eJetson Orin Nano 8GB\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgba(127,127,127,0.3); padding: 14px; text-align: center; background: rgba(127,127,127,0.10);\"\u003eJetson Orin NX 8GB\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgba(127,127,127,0.3); padding: 14px; text-align: center; background: rgba(127,127,127,0.10);\"\u003eJetson Orin NX 16GB\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003c!-- AI PERFORMANCE --\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 12px 14px; font-weight: bold; background: rgba(127, 127, 127, 0.07); text-align: center;\"\u003eAI Performance\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eSparse INT8 Performance — Standard\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 20 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 40 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 70 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 100 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eSparse INT8 Performance — MAXN_SUPER\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: bold; text-align: center;\"\u003eUp to 34 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: bold; text-align: center;\"\u003eUp to 67 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003eUp to 117 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003eUp to 157 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eDense INT8 Performance — Standard\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 10 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 20 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 35 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 50 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eDense INT8 Performance — MAXN_SUPER\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: bold; text-align: center;\"\u003eUp to 17 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: bold; text-align: center;\"\u003eUp to 33 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003eUp to 58 TOPS\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003eUp to 78 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c!-- GPU --\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 12px 14px; font-weight: bold; background: rgba(127, 127, 127, 0.07); text-align: center;\"\u003eGPU \u0026amp; CUDA\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eGPU Architecture\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eNVIDIA Ampere GPU\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eCUDA Cores\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e512\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1024\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1024\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1024\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eTensor Cores\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e16\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e32\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e32\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e32\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eGPU Frequency — Standard\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 625 MHz\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 765 MHz\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 918 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eGPU Frequency — MAXN_SUPER\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003eUp to 1020 MHz\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003eUp to 1173 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eFP32 Performance — Standard\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e0.64 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1.28 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1.56 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1.88 TFLOPs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eFP32 Performance — MAXN_SUPER\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1.04 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e2.08 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e2.40 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e2.40 TFLOPs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eFP16 Performance — Standard\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1.28 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e2.56 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e3.12 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e3.76 TFLOPs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eFP16 Performance — MAXN_SUPER\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e2.08 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e4.16 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e4.80 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e4.80 TFLOPs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c!-- CPU --\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 12px 14px; font-weight: bold; background: rgba(127, 127, 127, 0.07); text-align: center;\"\u003eCPU\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eCPU\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e6-core Arm Cortex-A78AE\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e6-core Arm Cortex-A78AE\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e8-core Arm Cortex-A78AE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eCPU Frequency — Standard\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 1.5 GHz\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 2.0 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eCPU Frequency — MAXN_SUPER\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 1.7 GHz\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 2.0 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c!-- MEMORY --\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 12px 14px; font-weight: bold; background: rgba(127, 127, 127, 0.07); text-align: center;\"\u003eMemory\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eLPDDR5 Memory\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e4GB\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e8GB\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e8GB\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e16GB\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eMemory Bus\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e64-bit\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e128-bit\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e128-bit\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eMemory Bandwidth — Standard\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e34 GB\/s\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e68 GB\/s\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e102 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eMemory Bandwidth — MAXN_SUPER\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003e51 GB\/s\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003e102 GB\/s\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e102 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c!-- VIDEO \/ DISPLAY --\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 12px 14px; font-weight: bold; background: rgba(127, 127, 127, 0.07); text-align: center;\"\u003eVideo \u0026amp; Display\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eVideo Decode\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eH.265 \/ H.264 \/ VP9 \/ AV1\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eH.265 \/ H.264 \/ VP9 \/ AV1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eVideo Encode\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e1080p30 via CPU software\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eH.265 \/ H.264 \/ AV1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eMaximum Display Resolution\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e3840 × 2160 @ 30 Hz\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e7680 × 4320 @ 30 Hz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c!-- INTERFACES --\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 12px 14px; font-weight: bold; background: rgba(127, 127, 127, 0.07); text-align: center;\"\u003eHigh-Speed Interfaces\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003ePCIe\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to PCIe Gen3\u003c\/td\u003e\n\u003ctd colspan=\"2\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to PCIe Gen4\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eUSB\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003eUp to 3 × USB 3.2 + 3 × USB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eMIPI CSI-2\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e8 lanes\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eGigabit Ethernet\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e10\/100\/1000 Mbps\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c!-- POWER --\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 12px 14px; font-weight: bold; background: rgba(127, 127, 127, 0.07); text-align: center;\"\u003ePower Modes\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eStandard Power Modes\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e7W \/ 10W\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e7W \/ 15W\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e10W \/ 15W \/ 20W\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e10W \/ 15W \/ 25W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eMAXN_SUPER Power Mode\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003e25W\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003e25W\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003e40W\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center; font-weight: bold;\"\u003e40W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003eOperating Temperature (TJ)\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e-25°C to 105°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgba(127, 127, 127, 0.3); padding: 13px 14px; font-weight: 600; text-align: center;\"\u003e24×7 Operating Lifetime\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"border: 1px solid rgba(127,127,127,0.3); padding: 13px 14px; text-align: center;\"\u003e5 Years\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c!-- SOFTWARE --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eNVIDIA Software Ecosystem\u003c\/h2\u003e\n\u003cp class=\"tr-section-intro\"\u003eJetson platforms provide an extensive software ecosystem for developing and deploying accelerated AI applications at the edge.\u003c\/p\u003e\n\u003cdiv class=\"tr-features\"\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eNVIDIA JetPack\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eSoftware stack for Jetson development, including system software, libraries and tools for accelerated AI applications.\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eNVIDIA Isaac\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eRobotics development platform supporting simulation, perception, navigation and accelerated robotics workloads.\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tr-feature\"\u003e\n\u003ch3 style=\"text-align: center;\"\u003e\u003cstrong\u003eNVIDIA Metropolis\u003c\/strong\u003e\u003c\/h3\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eAI-powered video analytics platform for smart spaces, industrial monitoring and computer vision applications.\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c!-- APPLICATIONS --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2\u003eApplications\u003c\/h2\u003e\n\u003cdiv class=\"tr-applications\"\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eRobotics\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eComputer Vision\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eIndustrial Automation\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eEdge AI\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eAutonomous Systems\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eSmart Surveillance\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eAI Inspection\u003c\/strong\u003e\u003c\/div\u003e\n\u003cdiv class=\"tr-application\"\u003e\u003cstrong\u003eEmbedded AI\u003c\/strong\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/section\u003e\n\u003c!-- PACKAGE CONTENTS --\u003e\n\u003csection class=\"tr-section\"\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003ePassive Cooling\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eDesigned for Jetson Orin NX \/ Nano with passive cooling\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/JETSON-ORIN-CASE-C-details-3_ab8f9cfd-f1a1-4f30-8a7b-1d957446f253.jpg?v=1788759933\" alt=\"\"\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003ePrecise Opening Design\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eExquisite manufacturing process, Fitting \u0026amp; Nice Looking\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/accessories\/JETSON-ORIN-CASE-C\/JETSON-ORIN-CASE-C-details-5.jpg\" alt=\"JETSON-ORIN-CASE-C, Precise Opening Design\"\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eOnboard Power Button With Indicator\u003c\/h2\u003e\n\u003ch2\u003e\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/accessories\/JETSON-ORIN-CASE-C\/JETSON-ORIN-CASE-C-details-7.jpg\" alt=\"JETSON-ORIN-CASE-C, Onboard Power Indicator\"\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eReserved Rail-Mount Buckle Mounting Holes\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eEasy to install to specific scenarios\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/accessories\/JETSON-ORIN-CASE-C\/JETSON-ORIN-CASE-C-details-9.jpg\" alt=\"JETSON-ORIN-CASE-C, Reserved rail mounting holes\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eOutline Dimensions\u003cbr\u003e\n\u003c\/h2\u003e\n\u003ch2\u003e\u003cimg src=\"https:\/\/www.waveshare.com\/img\/devkit\/accessories\/JETSON-ORIN-CASE-C\/JETSON-ORIN-CASE-C-details-size.jpg\" alt=\"JETSON-ORIN-CASE-C, outline dimensions\"\u003e\u003c\/h2\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2\u003eDocumentation \u0026amp; Resources\u003c\/h2\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse; border: 1px solid rgba(127, 127, 127, 0.35); font-family: inherit; color: inherit; background: transparent; height: 173.562px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"background: rgba(127, 127, 127, 0.08); height: 43.3906px;\"\u003e\n\u003cth style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); height: 43.3906px; width: 50.1789%; text-align: center;\"\u003eDocument\u003c\/th\u003e\n\u003cth style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); height: 43.3906px; width: 49.8211%; text-align: center;\"\u003eLink\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 43.3906px;\"\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; height: 43.3906px; width: 50.1789%;\"\u003eJetson Orin Nano Datasheet\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; height: 43.3906px; width: 49.8211%;\"\u003e\u003cspan style=\"text-decoration: underline; color: rgb(255, 42, 0);\"\u003e\u003cem\u003e\u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Jetson-Orin-Nano-Series-Modules-Datasheet_DS-11105-001_v1.7.pdf?v=1788762374\" style=\"color: rgb(255, 42, 0); text-decoration: underline;\" target=\"_blank\"\u003eView Datasheet\u003c\/a\u003e\u003c\/em\u003e\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 43.3906px;\"\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; height: 43.3906px; width: 50.1789%;\"\u003eJetson Orin NX Datasheet\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; height: 43.3906px; width: 49.8211%;\"\u003e\u003cspan style=\"text-decoration: underline; color: rgb(255, 42, 0);\"\u003e\u003cem\u003e\u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Jetson-Orin-NX-Series-Modules-Datasheet_DS-10712-001_v1.7.pdf?v=1788762375\" style=\"color: rgb(255, 42, 0); text-decoration: underline;\" target=\"_blank\"\u003eView Datasheet\u003c\/a\u003e\u003c\/em\u003e\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 43.3906px;\"\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; height: 43.3906px; width: 50.1789%;\"\u003eJetson Orin Nano \/ NX Flashing Guide\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; height: 43.3906px; width: 49.8211%;\"\u003e\u003cspan style=\"text-decoration: underline; color: rgb(255, 42, 0);\"\u003e\u003cem\u003e\u003ca href=\"https:\/\/www.waveshare.com\/wiki\/Jetson_Orin_Nano\" style=\"color: rgb(255, 42, 0); text-decoration: underline;\" target=\"_blank\"\u003eView Guide\u003c\/a\u003e\u003c\/em\u003e\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003ePackage Contents\u003c\/h2\u003e\n\u003cdiv class=\"tr-table-wrap\"\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse; border: 1px solid rgba(127,127,127,0.35); font-family: inherit; color: inherit; background: transparent;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"background: rgba(127,127,127,0.08);\"\u003e\n\u003cth style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 50.3559%;\"\u003eItem\u003c\/th\u003e\n\u003cth style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 49.6441%;\"\u003eQuantity\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 50.3559%;\"\u003e\u003cstrong\u003eSelected Jetson Orin Nano \/ Orin NX Module\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 49.6441%;\"\u003e\u003cstrong\u003e1\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 50.3559%;\"\u003eWaveshare Carrier Board\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 49.6441%;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 50.3559%;\"\u003eIndustrial-Grade Metal Enclosure\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 49.6441%;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 50.3559%;\"\u003e240GB NVMe SSD\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 49.6441%;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 50.3559%;\"\u003eWi-Fi + Bluetooth Module\u003c\/td\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 49.6441%;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px; border: 1px solid rgba(127, 127, 127, 0.35); text-align: center; width: 50.3559%;\"\u003eWireless 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