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NVIDIA Jetson Orin Nano Super Developer Kit - (Quantity Restrictions)
NVIDIA Jetson Orin™ Nano Super Developer Kit
The NVIDIA Jetson Orin Nano™ Super Developer Kit is a compact, yet powerful computer that redefines generative AI for small edge devices. It delivers up to 67 TOPS of AI performance—a 1.7X improvement over its predecessor—to seamlessly run the most popular generative AI models, like vision transformers, large language models, vision-language models, and more.
Note: Limit of two units per customer account. Educational institutions are exempt from this restriction.
For larger quantity needs, NVIDIA Jetson Orin™ Nano Deployment Kits
Features
AI Performance 67 TOPS
Memory Bandwidth 102 GB/s
CPU Frequency 1.7 GHz
GPU 1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores
CPU 6-core Arm® Cortex®-A78AE v8.2 64-bit CPU, 1.5MB L2 + 4MB L3
Memory 8GB 128-bit LPDDR5 @ 68 GB/s
Storage SD Card Slot & external NVMe via M.2 Key M
Power 7W – 25W
Jetson Orin Nano Super Developer Kit configuration
NVIDIA Jetson Orin Nano Developer Kit (original) NVIDIA Jetson Orin NanoSuper Developer Kit
GPU
1,020MHz
AI PERF
67 TOPS (Sparse)
CPU
6-core Arm Cortex-
6-core Arm Cortex-1.7 GHz
Memory
8GB 128-bit LPDDR5
8GB 128-bit LPDDR5102GB/s
MODULE POWER 7W|15W
7W|15W|25W
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{"id":8201881715005,"title":"NVIDIA Jetson Orin Nano Super Developer Kit - (Quantity Restrictions)","handle":"nvidia-jetson-orin-nano-developer-kit","description":"\u003ch2 style=\"text-align: center;\"\u003eNVIDIA Jetson Orin™ Nano Super Developer Kit\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cmeta charset=\"UTF-8\"\u003e\u003cspan\u003eThe NVIDIA Jetson Orin Nano™ Super Developer Kit is a compact, yet powerful computer that redefines generative AI for small edge devices. It delivers up to 67 TOPS of AI performance—a 1.7X improvement over its predecessor—to seamlessly run the most popular generative AI models, like vision transformers, large language models, vision-language models, and more. \u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\" data-end=\"188\" data-start=\"77\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e\u003cstrong data-end=\"86\" data-start=\"77\"\u003eNote:\u003c\/strong\u003e Limit of two units per customer account. \u003cem data-end=\"188\" data-start=\"128\"\u003eEducational institutions are exempt from this restriction.\u003c\/em\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\" data-end=\"276\" data-start=\"190\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eFor larger quantity needs, \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 data-end=\"261\" data-start=\"217\"\u003eNVIDIA Jetson Orin™ Nano Deployment Kits\u003c\/strong\u003e\u003c\/a\u003e\u003c\/em\u003e\u003c\/span\u003e are available.\u003c\/span\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\u003ctable style=\"width: 99.5588%;\" border=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e67 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eMemory Bandwidth\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e102 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eCPU Frequency\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e1.7 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e6-core Arm® Cortex®-A78AE v8.2 64-bit CPU, 1.5MB L2 + 4MB L3\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e8GB 128-bit LPDDR5 @ 68 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003eSD Card Slot \u0026amp; external NVMe via M.2 Key M\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003ePower\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e7W – 25W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\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\u003ctbody\u003e\n\u003ctr style=\"height: 56.9205px;\"\u003e\n\u003ctd style=\"text-align: center; width: 99.3512%; height: 56.9205px;\" height=\"46\" width=\"935\" colspan=\"3\" class=\"et3\"\u003e\n\u003ch3\u003eJetson Orin Nano Super Developer Kit configuration\u003c\/h3\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 122.983px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 122.983px;\" height=\"123\" width=\"262\" class=\"et5\"\u003e \u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 122.983px;\" width=\"351\" class=\"et6\"\u003e\u003cstrong\u003eNVIDIA Jetson Orin Nano Developer Kit (original)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 122.983px;\" width=\"320\" class=\"et6\"\u003e\u003cstrong\u003eNVIDIA Jetson Orin NanoSuper Developer Kit\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 273.949px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 273.949px;\" height=\"274\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 273.949px;\" width=\"351\" class=\"et5\"\u003e\n\u003cbr\u003eNVIDIA Ampere architecture\u003cbr\u003e1,024 CUDA Cores\u003cbr\u003e32 Tensor Cores\u003cbr\u003e635 MHz\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 273.949px;\" width=\"320\" class=\"et5\"\u003e\n\u003cbr\u003eNVIDIA Ampere\u003cbr\u003earchitecture\u003cbr\u003e1,024 CUDA Cores\u003cbr\u003e32 Tensor Cores\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e1,020MHz\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 180px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 180px;\" height=\"180\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eAI PERF\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 180px;\" width=\"351\" class=\"et5\"\u003e\n\u003cbr\u003e40 INT8 TOPS (Sparse)\u003cbr\u003e20 INT8 TOPS (Dense)\u003cbr\u003e10 FP16 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 180px;\" width=\"320\" class=\"et5\"\u003e\n\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e67 TOPS (Sparse)\u003cbr\u003e33 TOPS (Dense)\u003cbr\u003e17 FP16 TFLOPs\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 150.966px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 150.966px;\" height=\"151\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 150.966px;\" width=\"351\" class=\"et5\"\u003e6-core Arm Cortex-\u003cbr\u003eA78AE v8.264-bit CPU\u003cbr\u003e1.5 GHz\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 150.966px;\" width=\"320\" class=\"et5\"\u003e6-core Arm Cortex-\u003cbr\u003eA78AE v8.264-bit CPU\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e1.7 GHz\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 125px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 125px;\" height=\"125\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 125px;\" width=\"351\" class=\"et5\"\u003e8GB 128-bit LPDDR5\u003cbr\u003e68GB\/s\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 125px;\" width=\"320\" class=\"et5\"\u003e8GB 128-bit LPDDR5\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e102GB\/s\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 47.9972px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 47.9972px;\" height=\"48\" width=\"262\" class=\"et6\"\u003e\u003cstrong\u003eMODULE POWER\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 47.9972px;\" width=\"351\" class=\"et5\"\u003e7W|15W\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 47.9972px;\" width=\"320\" class=\"et5\"\u003e7W|15W|\u003cstrong\u003e\u003cspan class=\"font1\"\u003e25W\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","published_at":"2023-03-30T10:20:56+05:30","created_at":"2023-03-27T18:34:13+05:30","vendor":"NVIDIA","type":"","tags":["jetson","Jetson GPU","Jetson module","jetson nano","Jetson Nano development kit","nano 8GB","NVDA","nvidia","nvidia gpu","nvidia jetson","NVIDIA nano","ORIN","orin 8GB","orin nano","ZOHO UPDATED"],"price":3099999,"price_min":3099999,"price_max":3099999,"available":false,"price_varies":false,"compare_at_price":3299999,"compare_at_price_min":3299999,"compare_at_price_max":3299999,"compare_at_price_varies":false,"variants":[{"id":44900111188285,"title":"Default Title","option1":"Default Title","option2":null,"option3":null,"sku":"SBC1047","requires_shipping":true,"taxable":true,"featured_image":null,"available":false,"name":"NVIDIA Jetson Orin Nano Super Developer Kit - (Quantity Restrictions)","public_title":null,"options":["Default Title"],"price":3099999,"weight":2000,"compare_at_price":3299999,"inventory_management":"shopify","barcode":"SBC1047","requires_selling_plan":false,"selling_plan_allocations":[]}],"images":["\/\/thinkrobotics.com\/cdn\/shop\/files\/jetson-orin-nano-super-developer-kit-og.jpg?v=1737536404","\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-3QTR-Front-Left-_1.jpg?v=1737536404","\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-Back-SD.jpg?v=1737536404","\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-3QTR-Front-Left-_2.jpg?v=1737536404"],"featured_image":"\/\/thinkrobotics.com\/cdn\/shop\/files\/jetson-orin-nano-super-developer-kit-og.jpg?v=1737536404","options":["Title"],"media":[{"alt":null,"id":42739253575997,"position":1,"preview_image":{"aspect_ratio":1.905,"height":630,"width":1200,"src":"\/\/thinkrobotics.com\/cdn\/shop\/files\/jetson-orin-nano-super-developer-kit-og.jpg?v=1737536404"},"aspect_ratio":1.905,"height":630,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/files\/jetson-orin-nano-super-developer-kit-og.jpg?v=1737536404","width":1200},{"alt":null,"id":33238009020733,"position":2,"preview_image":{"aspect_ratio":1.0,"height":600,"width":600,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-3QTR-Front-Left-_1.jpg?v=1737536404"},"aspect_ratio":1.0,"height":600,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-3QTR-Front-Left-_1.jpg?v=1737536404","width":600},{"alt":null,"id":33238008987965,"position":3,"preview_image":{"aspect_ratio":1.0,"height":600,"width":600,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-Back-SD.jpg?v=1737536404"},"aspect_ratio":1.0,"height":600,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-Back-SD.jpg?v=1737536404","width":600},{"alt":null,"id":33238008955197,"position":4,"preview_image":{"aspect_ratio":1.0,"height":600,"width":600,"src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-3QTR-Front-Left-_2.jpg?v=1737536404"},"aspect_ratio":1.0,"height":600,"media_type":"image","src":"\/\/thinkrobotics.com\/cdn\/shop\/products\/NVIDIA-JetsonOrin-3QTR-Front-Left-_2.jpg?v=1737536404","width":600}],"requires_selling_plan":false,"selling_plan_groups":[],"content":"\u003ch2 style=\"text-align: center;\"\u003eNVIDIA Jetson Orin™ Nano Super Developer Kit\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cmeta charset=\"UTF-8\"\u003e\u003cspan\u003eThe NVIDIA Jetson Orin Nano™ Super Developer Kit is a compact, yet powerful computer that redefines generative AI for small edge devices. It delivers up to 67 TOPS of AI performance—a 1.7X improvement over its predecessor—to seamlessly run the most popular generative AI models, like vision transformers, large language models, vision-language models, and more. \u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\" data-end=\"188\" data-start=\"77\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e\u003cstrong data-end=\"86\" data-start=\"77\"\u003eNote:\u003c\/strong\u003e Limit of two units per customer account. \u003cem data-end=\"188\" data-start=\"128\"\u003eEducational institutions are exempt from this restriction.\u003c\/em\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\" data-end=\"276\" data-start=\"190\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003eFor larger quantity needs, \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 data-end=\"261\" data-start=\"217\"\u003eNVIDIA Jetson Orin™ Nano Deployment Kits\u003c\/strong\u003e\u003c\/a\u003e\u003c\/em\u003e\u003c\/span\u003e are available.\u003c\/span\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\u003ctable style=\"width: 99.5588%;\" border=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eAI Performance\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e67 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eMemory Bandwidth\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e102 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eCPU Frequency\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e1.7 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e6-core Arm® Cortex®-A78AE v8.2 64-bit CPU, 1.5MB L2 + 4MB L3\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e8GB 128-bit LPDDR5 @ 68 GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003eSD Card Slot \u0026amp; external NVMe via M.2 Key M\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: center; width: 50.8804%;\"\u003e\u003cstrong\u003ePower\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 48.6613%;\"\u003e7W – 25W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\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\u003ctbody\u003e\n\u003ctr style=\"height: 56.9205px;\"\u003e\n\u003ctd style=\"text-align: center; width: 99.3512%; height: 56.9205px;\" height=\"46\" width=\"935\" colspan=\"3\" class=\"et3\"\u003e\n\u003ch3\u003eJetson Orin Nano Super Developer Kit configuration\u003c\/h3\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 122.983px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 122.983px;\" height=\"123\" width=\"262\" class=\"et5\"\u003e \u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 122.983px;\" width=\"351\" class=\"et6\"\u003e\u003cstrong\u003eNVIDIA Jetson Orin Nano Developer Kit (original)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 122.983px;\" width=\"320\" class=\"et6\"\u003e\u003cstrong\u003eNVIDIA Jetson Orin NanoSuper Developer Kit\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 273.949px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 273.949px;\" height=\"274\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eGPU\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 273.949px;\" width=\"351\" class=\"et5\"\u003e\n\u003cbr\u003eNVIDIA Ampere architecture\u003cbr\u003e1,024 CUDA Cores\u003cbr\u003e32 Tensor Cores\u003cbr\u003e635 MHz\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 273.949px;\" width=\"320\" class=\"et5\"\u003e\n\u003cbr\u003eNVIDIA Ampere\u003cbr\u003earchitecture\u003cbr\u003e1,024 CUDA Cores\u003cbr\u003e32 Tensor Cores\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e1,020MHz\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 180px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 180px;\" height=\"180\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eAI PERF\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 180px;\" width=\"351\" class=\"et5\"\u003e\n\u003cbr\u003e40 INT8 TOPS (Sparse)\u003cbr\u003e20 INT8 TOPS (Dense)\u003cbr\u003e10 FP16 TFLOPs\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 180px;\" width=\"320\" class=\"et5\"\u003e\n\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e67 TOPS (Sparse)\u003cbr\u003e33 TOPS (Dense)\u003cbr\u003e17 FP16 TFLOPs\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 150.966px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 150.966px;\" height=\"151\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eCPU\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 150.966px;\" width=\"351\" class=\"et5\"\u003e6-core Arm Cortex-\u003cbr\u003eA78AE v8.264-bit CPU\u003cbr\u003e1.5 GHz\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 150.966px;\" width=\"320\" class=\"et5\"\u003e6-core Arm Cortex-\u003cbr\u003eA78AE v8.264-bit CPU\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e1.7 GHz\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 125px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 125px;\" height=\"125\" width=\"262\" class=\"et6\"\u003e\n\u003cbr\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 125px;\" width=\"351\" class=\"et5\"\u003e8GB 128-bit LPDDR5\u003cbr\u003e68GB\/s\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 125px;\" width=\"320\" class=\"et5\"\u003e8GB 128-bit LPDDR5\u003cbr\u003e\u003cstrong\u003e\u003cspan class=\"font1\"\u003e102GB\/s\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 47.9972px;\"\u003e\n\u003ctd style=\"text-align: center; width: 27.4957%; height: 47.9972px;\" height=\"48\" width=\"262\" class=\"et6\"\u003e\u003cstrong\u003eMODULE POWER\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 35.3778%; height: 47.9972px;\" width=\"351\" class=\"et5\"\u003e7W|15W\u003c\/td\u003e\n\u003ctd style=\"text-align: center; width: 36.4776%; height: 47.9972px;\" width=\"320\" class=\"et5\"\u003e7W|15W|\u003cstrong\u003e\u003cspan class=\"font1\"\u003e25W\u003c\/span\u003e\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e"}
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