{"product_id":"nvidia-jetson-agx-orin-64gb-dev-kit-275-tops-ai-edge-computer","title":"NVIDIA Jetson AGX Orin 64GB Dev Kit 275 TOPS AI Edge Computer","description":"\u003cdiv\u003e\n\u003ch1\u003eNVIDIA Jetson AGX Orin 64GB Developer Kit - 275 TOPS AI Edge Computing Platform\u003c\/h1\u003e\n\u003cp\u003eThe \u003cstrong\u003eNVIDIA Jetson AGX Orin 64GB Developer Kit\u003c\/strong\u003e delivers a giant leap forward for robotics and edge AI development. With up to \u003cstrong\u003e275 TOPS of AI performance\u003c\/strong\u003e and power configurable between 15W and 60W, this compact developer kit provides more than 8 times the performance of Jetson AGX Xavier in the same form factor. Perfect for prototyping advanced AI-powered robots, autonomous machines, and intelligent vision systems.\u003c\/p\u003e\n\n\u003ch2\u003eWhy You'll Love the Jetson AGX Orin Developer Kit\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMassive AI Performance\u003c\/strong\u003e: Up to 275 TOPS enables deployment of large, complex AI models for natural language understanding, 3D perception, and multi-sensor fusion\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eNVIDIA Ampere GPU Architecture\u003c\/strong\u003e: 2048 CUDA cores and 64 Tensor cores deliver professional-grade AI compute at the edge\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eVersatile Development Platform\u003c\/strong\u003e: Emulates all Jetson Orin modules including Orin NX and Orin Nano, letting you prototype multiple product configurations with one kit\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eComprehensive Connectivity\u003c\/strong\u003e: PCIe Gen 4, 10GbE Ethernet, USB 3.2, M.2 NVMe, DisplayPort, and MIPI camera inputs provide extensive peripheral support\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e64GB Unified Memory\u003c\/strong\u003e: LPDDR5 memory with 204.8GB\/s bandwidth feeds multiple concurrent AI pipelines\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eComplete Software Stack\u003c\/strong\u003e: Includes JetPack SDK with support for Isaac for robotics, DeepStream for vision AI, and Riva for conversational AI\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003ePowerful AI Architecture for Edge Computing\u003c\/h2\u003e\n\u003cp\u003eAt the heart of the developer kit is the \u003cstrong\u003eJetson AGX Orin 64GB module\u003c\/strong\u003e, featuring a 12-core Arm Cortex-A78AE CPU running at up to 2.2GHz, combined with the NVIDIA Ampere architecture GPU. The module includes \u003cstrong\u003edual NVIDIA Deep Learning Accelerators (NVDLA v2.0)\u003c\/strong\u003e and a Programmable Vision Accelerator (PVA v2.0) for hardware-accelerated AI inferencing. This powerful combination supports multiple concurrent AI application pipelines for computer vision, natural language processing, and sensor fusion applications.\u003c\/p\u003e\n\n\u003ch2\u003eCompact Form Factor, Maximum Connectivity\u003c\/h2\u003e\n\u003cp\u003eDespite its powerful specifications, the Jetson AGX Orin Developer Kit measures just \u003cstrong\u003e110mm × 110mm × 72mm\u003c\/strong\u003e, making it incredibly compact for desktop prototyping. The reference carrier board provides extensive I\/O including:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e2 × USB 3.2 Gen 2 Type-A ports\u003c\/li\u003e\n\u003cli\u003e2 × USB 3.2 Gen 1 Type-A ports\u003c\/li\u003e\n\u003cli\u003e2 × USB 3.2 Gen 2 Type-C ports with USB PD (one for power input)\u003c\/li\u003e\n\u003cli\u003e1 × micro-USB 2.0 debug port\u003c\/li\u003e\n\u003cli\u003e10 Gigabit Ethernet (10GbE) RJ45\u003c\/li\u003e\n\u003cli\u003eDisplayPort 1.4a output supporting up to 8K60\u003c\/li\u003e\n\u003cli\u003ePCIe Gen 4 x16 mechanical slot (x8 electrical)\u003c\/li\u003e\n\u003cli\u003eM.2 Key M slot (PCIe Gen 4 x4) for NVMe SSD storage\u003c\/li\u003e\n\u003cli\u003eM.2 Key E slot (PCIe Gen 4 x1) with pre-installed 802.11ac Wi-Fi and Bluetooth 5.0 module\u003c\/li\u003e\n\u003cli\u003eMicroSD card slot\u003c\/li\u003e\n\u003cli\u003e120-pin MIPI CSI-2 camera connector supporting up to 6 cameras (16 via virtual channels)\u003c\/li\u003e\n\u003cli\u003e40-pin GPIO expansion header with I2C, SPI, UART, CAN, I2S, PWM, and GPIO\u003c\/li\u003e\n\u003cli\u003eJTAG debug port\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eIdeal for Professional AI Development\u003c\/h2\u003e\n\u003cp\u003eThe Jetson AGX Orin 64GB is purpose-built for demanding edge AI applications across industries including \u003cstrong\u003eautonomous robotics, industrial automation, smart cities, healthcare imaging, retail analytics, and agricultural technology\u003c\/strong\u003e. The configurable power modes allow you to balance performance and thermal requirements for your specific application, while the comprehensive JetPack SDK provides optimised libraries for CUDA, TensorRT, cuDNN, and computer vision frameworks.\u003c\/p\u003e\n\n\u003ch2\u003eComplete Development Environment\u003c\/h2\u003e\n\u003cp\u003eNVIDIA provides extensive software support through the \u003cstrong\u003eJetPack SDK\u003c\/strong\u003e, which includes Linux for Tegra (L4T) based on Ubuntu 22.04, CUDA toolkit, TensorRT for optimised inference, cuDNN for deep learning, VPI for computer vision, and multimedia APIs. Pre-trained models are available through the NGC catalog, and the NVIDIA TAO toolkit enables transfer learning and model fine-tuning. Omniverse Replicator supports synthetic data generation for training.\u003c\/p\u003e\n\n\u003ch2\u003eWhat's in the Box\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eNVIDIA Jetson AGX Orin 64GB module with heatsink (pre-installed on carrier board)\u003c\/li\u003e\n\u003cli\u003eReference carrier board (P3737)\u003c\/li\u003e\n\u003cli\u003e802.11ac\/abgn dual-band Wi-Fi and Bluetooth 5.0 module (pre-installed in M.2 Key E slot)\u003c\/li\u003e\n\u003cli\u003e90W USB-C power adapter with international plugs\u003c\/li\u003e\n\u003cli\u003eQuick start guide\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eFull Specifications\u003c\/h2\u003e\n\n\u003ch3\u003eCompute Performance\u003c\/h3\u003e\n\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eAI Performance\u003c\/td\u003e\n\u003ctd\u003eUp to 275 TOPS (INT8)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eGPU\u003c\/td\u003e\n\u003ctd\u003e2048-core NVIDIA Ampere architecture with 64 Tensor Cores, up to 1.3GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCPU\u003c\/td\u003e\n\u003ctd\u003e12-core Arm Cortex-A78AE (ARMv8.2) 64-bit CPU, up to 2.2GHz, 3MB L2 + 6MB L3 cache\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAI Accelerators\u003c\/td\u003e\n\u003ctd\u003e2 × NVIDIA Deep Learning Accelerator (NVDLA) v2.0, 1 × Programmable Vision Accelerator (PVA) v2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory\u003c\/td\u003e\n\u003ctd\u003e64GB LPDDR5, 256-bit, 204.8GB\/s bandwidth\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eStorage\u003c\/td\u003e\n\u003ctd\u003e64GB eMMC 5.1 (onboard module)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\n\u003ch3\u003eConnectivity \u0026amp; I\/O\u003c\/h3\u003e\n\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eNetworking\u003c\/td\u003e\n\u003ctd\u003e10 Gigabit Ethernet (10GbE), 802.11ac 2x2 Wi-Fi, Bluetooth 5.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eUSB Ports\u003c\/td\u003e\n\u003ctd\u003e2 × USB 3.2 Gen 2 Type-A, 2 × USB 3.2 Gen 1 Type-A, 2 × USB 3.2 Gen 2 Type-C with USB PD, 1 × micro-USB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDisplay Output\u003c\/td\u003e\n\u003ctd\u003e1 × DisplayPort 1.4a (up to 8K60)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePCIe Expansion\u003c\/td\u003e\n\u003ctd\u003e1 × PCIe Gen 4 x16 slot (x8 electrical), 1 × M.2 Key M (PCIe Gen 4 x4), 1 × M.2 Key E (PCIe Gen 4 x1)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eCamera Input\u003c\/td\u003e\n\u003ctd\u003e120-pin MIPI CSI-2 connector, 16-lane, D-PHY 2.1 (up to 40Gbps) or C-PHY 2.0 (up to 164Gbps)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eExpansion Header\u003c\/td\u003e\n\u003ctd\u003e40-pin GPIO with I2C, SPI, UART, CAN, I2S, PWM, GPIO\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOther\u003c\/td\u003e\n\u003ctd\u003eMicroSD card slot, JTAG debug connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\n\u003ch3\u003ePower \u0026amp; Physical\u003c\/h3\u003e\n\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower Input\u003c\/td\u003e\n\u003ctd\u003eUSB Type-C (USB PD) or DC barrel jack (9-20V)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower Consumption\u003c\/td\u003e\n\u003ctd\u003eConfigurable 15W to 60W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDimensions\u003c\/td\u003e\n\u003ctd\u003e110mm × 110mm × 72mm (4.3\" × 4.3\" × 2.8\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOperating Temperature\u003c\/td\u003e\n\u003ctd\u003e0°C to 50°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\n\u003ch3\u003eSoftware\u003c\/h3\u003e\n\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eOperating System\u003c\/td\u003e\n\u003ctd\u003eLinux for Tegra (L4T) based on Ubuntu 22.04 LTS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSDK\u003c\/td\u003e\n\u003ctd\u003eJetPack 5.x and later\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAI Frameworks\u003c\/td\u003e\n\u003ctd\u003eTensorFlow, PyTorch, MXNet, ONNX Runtime via NGC containers\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAI Tools\u003c\/td\u003e\n\u003ctd\u003eTensorRT, cuDNN, CUDA Toolkit, DeepStream SDK, Isaac SDK, Riva SDK\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eComputer Vision\u003c\/td\u003e\n\u003ctd\u003eVPI (Vision Programming Interface), OpenCV\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMultimedia\u003c\/td\u003e\n\u003ctd\u003eHardware-accelerated video encode\/decode (H.265, H.264, VP9)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\n\n\u003cp\u003e\u003cem\u003eSpecifications are sourced from the official NVIDIA developer documentation and may be updated. Visit developer.nvidia.com for the latest information.\u003c\/em\u003e\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Nvidia","offers":[{"title":"Default Title","offer_id":44324905975886,"sku":"PA-NVIDIAJETSONAGXOR-2","price":5640.0,"currency_code":"AUD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0676\/3134\/9838\/files\/Jetson-AGX-Orin-Dev-Kit-whiteBG.jpg?v=1789260366","url":"https:\/\/projectorsaustralia.com.au\/products\/nvidia-jetson-agx-orin-64gb-dev-kit-275-tops-ai-edge-computer","provider":"Projectors Australia","version":"1.0","type":"link"}