{"product_id":"nvidia-jetson-agx-thor-developer-kit","title":"NVIDIA Jetson AGX Thor Developer Kit 128GB LPDDR5x, 2070 FP4 TFLOPS, 1TB NVMe SSD, Wi‑Fi 6E","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eThe NVIDIA Jetson AGX Thor \u003cstrong\u003edeveloper kit\u003c\/strong\u003e is a Blackwell-architecture computing platform for robotics and edge AI development. It provides up to \u003cstrong\u003e2070 FP4 TFLOPS\u003c\/strong\u003e of AI compute and is specified as \u003cstrong\u003e7.5x\u003c\/strong\u003e higher performance than the previous-generation Jetson AGX Orin, with \u003cstrong\u003e3.5x\u003c\/strong\u003e higher energy efficiency. The kit is equipped with \u003cstrong\u003e128GB LPDDR5x\u003c\/strong\u003e memory (256-bit) with \u003cstrong\u003e273GB\/s\u003c\/strong\u003e bandwidth to support large Transformer inference, high-concurrency video encode\/decode, and multi-sensor data fusion.\u003c\/p\u003e\u003cp\u003eBlackwell \u003cstrong\u003emulti-instance GPU (MIG)\u003c\/strong\u003e is supported, allowing a single GPU to be partitioned into multiple isolated instances for concurrent workloads such as environment awareness, language interaction, and action planning. The platform integrates with the CUDA ecosystem and supports NVIDIA software stacks including \u003cstrong\u003eIsaac\u003c\/strong\u003e, \u003cstrong\u003eIsaac GR00T\u003c\/strong\u003e, \u003cstrong\u003eMetropolis\u003c\/strong\u003e, and \u003cstrong\u003eHoloscan\u003c\/strong\u003e.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAI performance:\u003c\/strong\u003e up to 2070 FP4 TFLOPS\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eGPU architecture:\u003c\/strong\u003e NVIDIA Blackwell\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCPU:\u003c\/strong\u003e 14-core Arm Neoverse V3AE\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMemory:\u003c\/strong\u003e 128GB LPDDR5x, 256-bit; memory bandwidth 273GB\/s\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePower consumption:\u003c\/strong\u003e 40–130W (130W also stated for 2070 FP4 TFLOPS operation)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eStorage (noted):\u003c\/strong\u003e 1TB NVMe SSD; SSD enclosure is provided for writing a system image\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWireless (on-board):\u003c\/strong\u003e Wi‑Fi (2.4GHz\/5GHz\/6GHz) up to 2402Mbps; Bluetooth 5.3; installed inside the device before shipment\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSystem image (noted):\u003c\/strong\u003e SSD is supplied with a pre-installed system image; the system image mentions AI visual functions, ROS cases, offline large model cases, and OpenClaw course content\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eProduct\u003c\/td\u003e\n\u003ctd\u003eJetson AGX Thor Developer Kit\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eGPU\u003c\/td\u003e\n\u003ctd\u003eNVIDIA Jetson T5000 with Blackwell GPU\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAI compute\u003c\/td\u003e\n\u003ctd\u003eUp to 2070 FP4 TFLOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCPU\u003c\/td\u003e\n\u003ctd\u003e14 cores (Arm Neoverse V3AE)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory\u003c\/td\u003e\n\u003ctd\u003e128GB LPDDR5x, 256-bit\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory bandwidth\u003c\/td\u003e\n\u003ctd\u003e273GB\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower consumption\u003c\/td\u003e\n\u003ctd\u003e40–130W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCooling\u003c\/td\u003e\n\u003ctd\u003eHeatsink and fan (fan and radiator)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eStorage (noted)\u003c\/td\u003e\n\u003ctd\u003e1TB NVMe SSD\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWireless\u003c\/td\u003e\n\u003ctd\u003eWi‑Fi 2.4GHz\/5GHz\/6GHz up to 2402Mbps; BT 5.3; Wi‑Fi 6E module noted\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eExternal I\/O (noted)\u003c\/td\u003e\n\u003ctd\u003e2x USB‑A; 2x USB‑C; RJ45 connector (5GbE); DP connector; HDMI 2.1 connector; QSFP28 connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eButtons\/indicators\u003c\/td\u003e\n\u003ctd\u003ePower button; flashing button; reset button; power indicator light\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eInternal headers \/ interfaces (noted)\u003c\/td\u003e\n\u003ctd\u003eAudio (10Pin); Automation Interface (12Pin); CAN Bus (2x13Pin); USB Type‑C Debugging Interface; JTAG (10Pin); RTC (2Pin)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eChassis dimensions\u003c\/td\u003e\n\u003ctd\u003e243 x 112.40 x 56.88 mm (units: mm); also noted length 240.86 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e3D model\u003c\/td\u003e\n\u003ctd\u003e3D model file will be provided\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\u003ch2\u003ePerformance Data (as stated)\u003c\/h2\u003e\u003ch3\u003eGenerative reasoning comparison notes\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003eCompared to Jetson AGX Orin, Jetson AGX Thor offers up to \u003cstrong\u003e5x\u003c\/strong\u003e faster for generative reasoning.\u003c\/li\u003e\n\u003cli\u003eWith \u003cstrong\u003eFP4\u003c\/strong\u003e and \u003cstrong\u003especulative decoding\u003c\/strong\u003e, developers are stated to achieve an additional \u003cstrong\u003e2x\u003c\/strong\u003e performance acceleration on Jetson AGX Thor.\u003c\/li\u003e\n\u003cli\u003eReal-time multimodal AI example notes: using Qwen2.5‑VL‑3B VLM and Llama3.2 3B LLM, initial Token (TTFT) responses are stated to be below \u003cstrong\u003e200 ms\u003c\/strong\u003e, and each Token (TPOT) output time is stated to be far below \u003cstrong\u003e50 ms\u003c\/strong\u003e.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eTokens\/s table (Jetson AGX Orin vs Jetson AGX Thor)\u003c\/h3\u003e\u003ctable\u003e\n\u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eFamily\u003c\/th\u003e\n\u003cth\u003eModel\u003c\/th\u003e\n\u003cth\u003eJetson AGX Orin (Tokens\/s)\u003c\/th\u003e\n\u003cth\u003eJetson AGX Thor (Tokens\/s)\u003c\/th\u003e\n\u003cth\u003eAcceleration Multiplier\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eLlama\u003c\/td\u003e\n\u003ctd\u003eLlama 3.1 8B\u003c\/td\u003e\n\u003ctd\u003e112.33\u003c\/td\u003e\n\u003ctd\u003e150.8\u003c\/td\u003e\n\u003ctd\u003e1.34\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eLlama\u003c\/td\u003e\n\u003ctd\u003eLlama 3.3 70B\u003c\/td\u003e\n\u003ctd\u003e7.38\u003c\/td\u003e\n\u003ctd\u003e12.64\u003c\/td\u003e\n\u003ctd\u003e1.71\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eQwen\u003c\/td\u003e\n\u003ctd\u003eQwen3-30B-A3B\u003c\/td\u003e\n\u003ctd\u003e76.69\u003c\/td\u003e\n\u003ctd\u003e226.42\u003c\/td\u003e\n\u003ctd\u003e2.95\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eQwen\u003c\/td\u003e\n\u003ctd\u003eQwen3-32B\u003c\/td\u003e\n\u003ctd\u003e16.84\u003c\/td\u003e\n\u003ctd\u003e79.1\u003c\/td\u003e\n\u003ctd\u003e4.7\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDeepSeek\u003c\/td\u003e\n\u003ctd\u003eDeepSeek-R1-Distill-Qwen-7B\u003c\/td\u003e\n\u003ctd\u003e180.41\u003c\/td\u003e\n\u003ctd\u003e304.76\u003c\/td\u003e\n\u003ctd\u003e1.69\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDeepSeek\u003c\/td\u003e\n\u003ctd\u003eDeepSeek-R1-Distill-Qwen-32B\u003c\/td\u003e\n\u003ctd\u003e16.96\u003c\/td\u003e\n\u003ctd\u003e82.63\u003c\/td\u003e\n\u003ctd\u003e4.87\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eQwen (VLM)\u003c\/td\u003e\n\u003ctd\u003eQwen2.5-VL-3B\u003c\/td\u003e\n\u003ctd\u003e216\u003c\/td\u003e\n\u003ctd\u003e356.86\u003c\/td\u003e\n\u003ctd\u003e1.65\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eQwen (VLM)\u003c\/td\u003e\n\u003ctd\u003eQwen2.5-VL-7B\u003c\/td\u003e\n\u003ctd\u003e154.02\u003c\/td\u003e\n\u003ctd\u003e252\u003c\/td\u003e\n\u003ctd\u003e1.64\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eLlama (VLM)\u003c\/td\u003e\n\u003ctd\u003eLlama 3.2 11B Vision\u003c\/td\u003e\n\u003ctd\u003e44.22\u003c\/td\u003e\n\u003ctd\u003e69.63\u003c\/td\u003e\n\u003ctd\u003e1.57\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eGR00T (VLA)\u003c\/td\u003e\n\u003ctd\u003eGR00T N1\u003c\/td\u003e\n\u003ctd\u003e18.5\u003c\/td\u003e\n\u003ctd\u003e46.7\u003c\/td\u003e\n\u003ctd\u003e2.52\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eGR00T (VLA)\u003c\/td\u003e\n\u003ctd\u003eGR00T N1.5\u003c\/td\u003e\n\u003ctd\u003e15.2\u003c\/td\u003e\n\u003ctd\u003e41.5\u003c\/td\u003e\n\u003ctd\u003e2.74\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\u003ch2\u003ePorts \u0026amp; Functional Distribution (as labeled)\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eDC power supply\u003c\/li\u003e\n\u003cli\u003eUSB Type‑C interface (can be used as a power input interface)\u003c\/li\u003e\n\u003cli\u003eHDMI\u003c\/li\u003e\n\u003cli\u003eUSB Type‑A interface\u003c\/li\u003e\n\u003cli\u003eDP interface\u003c\/li\u003e\n\u003cli\u003eEthernet port\u003c\/li\u003e\n\u003cli\u003eQSFP28 connector\u003c\/li\u003e\n\u003cli\u003eFan and radiator\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eSystem Image \u0026amp; Software Environment (as stated)\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eSSD has pre-installed system image.\u003c\/strong\u003e\u003c\/li\u003e\n\u003cli\u003eJetson AGX Thor comes with a \u003cstrong\u003e1TB empty SSD before shipment\u003c\/strong\u003e and an \u003cstrong\u003eSSD enclosure\u003c\/strong\u003e is provided for writing the system image file.\u003c\/li\u003e\n\u003cli\u003eA \u003cstrong\u003e2TB SSD\u003c\/strong\u003e with a system image file is also mentioned. If choosing the 2TB SSD version kit, the original 1TB SSD that comes with the official kit is stated to be retained; the 2TB SSD in the package must be replaced by the user, and the original packaging will not be removed by default.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eUbuntu 24.04-based\u003c\/strong\u003e Jetson system image is stated, with support for \u003cstrong\u003eNVIDIA CUDA 13.0\u003c\/strong\u003e, \u003cstrong\u003eTensorRT 10.13\u003c\/strong\u003e, \u003cstrong\u003ecuDNN 9.12\u003c\/strong\u003e, and \u003cstrong\u003eOpenCV 4.13\u003c\/strong\u003e.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eOptional \/ Supported Modules (as described)\u003c\/h2\u003e\u003ch3\u003eAI large model voice module (support stated)\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003eHigh-performance microphone and cavity speaker\u003c\/li\u003e\n\u003cli\u003eFar-field pickup, echo cancellation, and environmental noise reduction\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eUSB industrial camera (support stated)\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e5MP\u003c\/li\u003e\n\u003cli\u003eSupports stable output of 30fps at 2592 x 1944\u003c\/li\u003e\n\u003cli\u003e105° diagonal field of view (horizontal 81.8°, vertical 66°C as stated)\u003c\/li\u003e\n\u003cli\u003eDistortion-free images; dust-proof shell (as stated)\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eTutorial Video\u003c\/h2\u003e\u003cp\u003e\u003ciframe height=\"751\" src=\"https:\/\/www.youtube.com\/embed\/-20a1fotbZA\" title=\"Jetson AGX Thor: 2070 TFLOPS of Edge AI Power (Full Demo)\" width=\"1335\"\u003e\u003c\/iframe\u003e\u003c\/p\u003e\u003ch2\u003eSupport\u003c\/h2\u003e\u003cp\u003eFor technical questions or help choosing the right configuration for the Jetson AGX Thor developer kit, contact support at \u003ca href=\"https:\/\/rcdrone.top\/\"\u003ehttps:\/\/rcdrone.top\/\u003c\/a\u003e or \u003ca href=\"mailto:support@rcdrone.top\"\u003esupport@rcdrone.top\u003c\/a\u003e.\u003c\/p\u003e\u003ch2 id=\"details\"\u003eDetails\u003c\/h2\u003e\u003cdiv class=\"details-gallery\"\u003e\n\u003cimg alt=\"NVIDIA Jetson AGX Thor developer kit with 1TB NVMe system image note and onboard Wi‑Fi 6E card detail\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4.jpg?v=1782281427\"\u003e\u003cp\u003eThe included 1TB NVMe SSD ships with a pre-installed system image, and the onboard wireless card supports Wi‑Fi 6E plus Bluetooth 5.3.\u003c\/p\u003e\n\u003cimg alt=\"Jetson AGX Thor course and tutorial portal screen, listing developer kit learning categories and resources\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_cf2878a0-9f1b-4390-98f4-5b4c97cba6c9.jpg?v=1782281433\"\u003e\u003cimg alt=\"Jetson AGX Thor training outline with ROS, vision, LLM, and OpenClaw course modules listed in a long table\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_827b4494-4e1a-476c-8b46-ff97c7257ae5.jpg?v=1782281439\"\u003e\u003cimg alt=\"Folders for detailed tutorials and open-source code, plus basic setup, vision, and ROS advanced tutorial lists\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_23740e96-5bcb-49cd-b6d8-1e44ed4eb5a0.jpg?v=1782281446\"\u003e\u003cimg alt=\"Offline and online AI large model development materials with demos for text-to-picture, vision, and localization tasks\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_1bf3064d-c203-4573-99b9-5080d7c42d61.jpg?v=1782281452\"\u003e\u003cimg alt=\"Offline generative AI application materials with example projects like storytelling, cooking assistant, homework, and animation\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_79e3a071-2214-4073-b2d6-e45d706a3fc0.jpg?v=1782281458\"\u003e\u003cimg alt=\"OpenClaw advanced AI development materials with examples for file management, camera control, browser control, and coding\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_8cc625d4-7292-446e-a945-86275f35f03f.jpg?v=1782281465\"\u003e\u003cimg alt=\"Jetson AGX Thor kit connected to AI voice module and USB industrial camera, highlighting supported accessories\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_ee3e36a0-fc30-467e-9211-039c8c78a480.jpg?v=1782281471\"\u003e\u003cp\u003eBuild voice-enabled assistants or vision pipelines using supported peripherals like an AI voice module and USB industrial cameras.\u003c\/p\u003e\n\u003cimg alt=\"Jetson AGX Thor developer kit angled view with rear I\/O ports visible and AI model ecosystem logos above\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_ff8c71db-a82a-42cd-867c-d8db436f32cd.jpg?v=1782281476\"\u003e\u003cimg alt=\"Performance charts comparing Jetson AGX Thor vs Orin for generative reasoning and real-time multimodal token response\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_8367d40c-19ef-4fb0-90fa-1a3cd1800c15.jpg?v=1782281483\"\u003e\u003cp\u003ePerformance charts summarize generative reasoning gains and multimodal throughput targets for edge inference workloads.\u003c\/p\u003e\n\u003cimg alt=\"Jetson AGX Thor benchmark table and key specs callout: up to 2070 FP4 TFLOPS, 128GB LPDDR5x, 14-core CPU\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_e9874dc8-80b9-4291-b15c-6b084274332f.jpg?v=1782281489\"\u003e\u003cp\u003eCore platform highlights include up to 2070 FP4 TFLOPS AI compute, 128GB LPDDR5x memory, and a 14-core Arm CPU.\u003c\/p\u003e\n\u003cimg alt=\"Robotics and edge AI stack overview for Jetson AGX Thor, with sensor processing, low-latency pipeline, and software icons\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_cf37e8be-768c-4f5f-9aea-8760a6d88b4c.jpg?v=1782281495\"\u003e\u003cimg alt=\"Jetson AGX Thor functional distribution diagram labeling ports, buttons, cooling, and internal headers like CAN and JTAG\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_e41af2f0-4be5-494a-b1ba-7178e1dcef64.jpg?v=1782281501\"\u003e\u003cp\u003eA clear port-and-header map helps plan integration, from USB and display outputs to CAN bus, debug, and other internal interfaces.\u003c\/p\u003e\n\u003cimg alt=\"Jetson AGX Thor dimensions drawing in millimeters with 3D model availability note beneath the chassis rendering\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_0e9d0655-207f-4002-9208-904f5d3cfc0a.jpg?v=1782281507\"\u003e\u003cp\u003eMechanical drawings list the chassis dimensions in millimeters, and a 3D model file is available for enclosure design.\u003c\/p\u003e\n\u003cimg alt=\"System image screen noting Ubuntu 24.04-based Jetson system with CUDA, TensorRT, cuDNN, and OpenCV versions listed\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_3d0c8588-4b33-4531-8b9e-1d3e91a1368f.jpg?v=1782281514\"\u003e\u003cp\u003eThe updated system image is based on Ubuntu 24.04 and references common accelerated libraries in the CUDA software stack.\u003c\/p\u003e\n\u003cimg alt=\"Jetson full range comparison table highlighting Jetson AGX Thor column against Orin Nano, Orin NX, AGX Orin, and Xavier\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_109eba99-f3aa-4ced-ac4c-562999f256ff.jpg?v=1782281520\"\u003e\u003cimg alt=\"Continuation of Jetson comparison table with I\/O, networking, display, power, and dimensions across multiple Jetson models\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_2b32d987-a2f7-4961-8eee-93bb92945f25.jpg?v=1782281526\"\u003e\u003cimg alt=\"Jetson AGX Thor developer kit product photos with included power adapter and cables, plus retail box packaging\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_6521bc86-a135-4fba-bc9e-9930ab09f048.jpg?v=1782281531\"\u003e\u003cp\u003eIn the box: the Jetson AGX Thor developer kit, power supply, and necessary cables for initial bring-up.\u003c\/p\u003e\n\u003cimg alt=\"Shipping list graphic for NVIDIA Jetson AGX Thor 128GB developer kit with power adapter, USB-C cable, optional SSD and accessories\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_1469dd01-c4e7-4e5e-bb60-8fd9e514ad56.jpg?v=1782281538\"\u003e\u003cp\u003eThe Jetson AGX Thor 128GB developer kit ships with a power adapter and USB‑C data cable, with an optional 1TB\/2TB SSD and SSD enclosure, while the Vision Advanced Kit adds items like a DP‑to‑HDMI cable, USB industrial c​\u003c\/p\u003e\n\u003cimg alt=\"Jetson AGX Thor 128GB developer kit bundle contents with power adapter, USB-C cable, camera, hub, and accessories\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/Jetson-AGX-Thor-Developer-Kit-with-128GB-RAM2070-FP4_da022928-5444-4766-a00b-a247ab31517e.jpg?v=1782281544\"\u003e\u003cp\u003eJetson AGX Thor 128GB kit options bundle the board with a power adapter, USB‑C cable, DP‑to‑HDMI lead, USB industrial camera, SSD enclosure, USB 3.0 hub, and optional NVMe SSD and touchscreen add‑ons.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Yahboom","offers":[{"title":"1TB \/ Developer Kit","offer_id":53135903555808,"sku":"6000101391-1","price":6003.8,"currency_code":"USD","in_stock":true},{"title":"1TB \/ Vision Advanced Kit","offer_id":53135903588576,"sku":"6000101391-2","price":6134.6,"currency_code":"USD","in_stock":true},{"title":"1TB \/ AI Large Model Kit","offer_id":53135903621344,"sku":"6000101391-3","price":6170.6,"currency_code":"USD","in_stock":true},{"title":"1TB \/ Ultimate Kit","offer_id":53135903654112,"sku":"6000101391-4","price":6500.6,"currency_code":"USD","in_stock":true},{"title":"2TB \/ 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