reComputer J3011 - Edge AI Computer with NVIDIA® Jetson™ Orin™ Nano 8GB (Support Super Mode）

Features Brilliant AI Performance for Production: Achieves up to 40 TOPS AI performance with low power and latency, built by NVIDIA Orin SoC combining the NVIDIA Ampere™ GPU architecture with 64-bit operating capability, integrated advanced multi-function video and image processing, and NVIDIA Deep Learning Accelerators. Hand-Size Edge AI Device: Compact size at 130mm x120mm x 58.5mm, featuring an NVIDIA Jetson Orin Nano 8GB module, J401 carrier board, enclosure, and power adapter. Support desktop and wall mounting. Expandable with Rich I/Os: Includes 4x USB 3.2, HDMI 2.1, 2x CSI, 1x RJ45 for GbE, M.2 Key E, M.2 Key M, CAN, and GPIO. Accelerate Solutions to Market: Pre-installed JetPack 5.1.1 on 128GB NVMe SSD, Linux OS BSP, supporting Jetson software and leading AI frameworks. Scale to Deploy: support OTA, remote management services powered by Allxon and Balena. Flexible Customization: inlcudes changing accessories modules, logo, and hardware interfaces modification based on reComputer J3011 original design. Note For optimal performance with reComputer, we recommend using 128GB / 256GB / 512GB / 1TB SSDs from Seeed. Since some SSDs on the market may only be compatible with specific JetPack versions which may cause the device to fail to function properly, and this issue is also present with official NVIDIA dev kits. If you are looking for the version without power adapter, please check out reComputer J3011 without power adapter Specifications ● Jetson Orin Nano System on Module AI Performance reComputer J3011 - Jetson Orin Nano 8GB, 40 TOPS reComputer J3010 - Jetson Orin Nano 4GB, 20 TOPS GPU 1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores (Orin Nano 8GB) 512-core NVIDIA Ampere architecture GPU with 16 Tensor Cores (Orin Nano 4GB) CPU 6-core Arm® Cortex®-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB L3 Memory 8GB 128-bit LPDDR5 68 GB/s (Orin Nano 8GB) 4GB 64-bit LPDDR5 34 GB/s (Orin Nano 4GB) Video Encoder 1080p30 supported by 1-2 CPU cores Video Decoder 1x 4K60 (H.265) | 2x 4K30 (H.265) | 5x 1080p60 (H.265) | 11x 1080p30 (H.265) ● Carrier Board Storage 1x M.2 Key M PCIe (M.2 NVMe 2280 SSD 128G included) Networking Ethernet 1x RJ-45 Gigabit Ethernet (10/100/1000M) M.2 KEY E 1x M.2 Key E(pre-installed 1x Wi-Fi/Bluetooth combo module) I/O USB 4x USB 3.2 Type-A (10Gbps), 1x USB2.0 Type-C (Device Mode) Camera 2x CSI (2-lane 15pin) Display 1x HDMI 2.1 Fan 1x 4 pin Fan Connector (5V PWM) CAN 1x CAN Multifunctional Port 1x 40-Pin Expansion header 1x 12-Pin Control and UART header RTC 1x RTC 2-pin, supports CR1220 but not included Power 9-19V DC Mechanical Dimensions (W x D x H) 130mm x 120mm x 58.5mm (with case) Installation Desk, wall-mounting Operating Temperature -10℃~60℃ Warranty 1 Year Hardware overview reComputer J401 carrier board, included in the full system - reComputer J3011 Desktop, Wall Mount, Expandable or fit in anywhere Application Application Fields: AI Video Analytics Machine Vision Autonomous Mobile Robot (AMR) Generative AI ● Capable of Bringing Generatie AI to the Edge Now you can build AI agents capable of processing large amounts of live or archived videos and images with Vision-Language Models (VLM) such as LLaVA, this new AI agents help nearly every industry summarize, search, and extract actionable insights from video using natural language. ● Build Multi-streams AI Video Analytics For building video analytics, Jetson Orin Nano incorporates the NVIDIA Multi-Standard Video Decoder. This video decoder accelerates video decode, supporting low resolution mobile content, Standard Definition (SD), High Definition (HD) and UltraHD (8K, 4K, etc.) reComputer J3011 can take 13x1080p30 streams. See our tested YOLOv8 performance using NVIDIA Deepstream of single model and multi model on multi streams. ● Fastest Way to Deploy Generative AI and Computer Vision Models We 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.