{"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","url":"https:\/\/thinkrobotics.com\/ar\/products\/nvidia-jetson-agx-thor-developer-kit","provider":"Atlantis Robotics","version":"1.0","type":"link"}