{"product_id":"aibox-orinnano-67tops-ai-big-model-of-edge-computing-jetson-module-nvidia","title":"AIBOX-OrinNano Jetson Orin Nano Embedded PC","description":"\u003cp class=\"geo-summary\" style=\"font-size:1rem;line-height:1.65;margin:0 0 1.25rem;padding:0 0 1rem;border-bottom:1px solid #e5e7eb;color:#1f2937\"\u003e\u003cstrong\u003eAIBOX-OrinNano Jetson Orin Nano Embedded PC\u003c\/strong\u003e is a Firefly product sold by Ai-Paipai. Key specifications — Cpu: Hexa-core 64-bit ARM Cortex-A78AE v8.2 processor, up to… · Ai performance: 67 TOPS · Traditional network architectures: Traditional network architectures such as CNN, RNN, and… · Video output: 1×HDMI 2.1 (4K@60fps) · Usb: 2 × USB 3.0 (Max: 1A). Typical applications: edge AI inference, machine vision and industrial automation. Ai-Paipai (Shenzhen AiPaipai Intelligent Technology Co., Ltd.) is an authorized distributor providing local technical support, pre-installed SDK \/ OS images, OEM \/ ODM customization, and worldwide shipping.\u003c\/p\u003e \u003c!-- Firefly product tabs --\u003e \u003cdiv class=\"fx-tabs\" data-fx-tabs\u003e \u003cdiv class=\"fx-tablist\" role=\"tablist\"\u003e \u003cbutton class=\"fx-tab is-active\" role=\"tab\" data-fx-tab=\"0\"\u003eDescription\u003c\/button\u003e \u003cbutton class=\"fx-tab\" role=\"tab\" data-fx-tab=\"1\"\u003eWhat's Included\u003c\/button\u003e \u003cbutton class=\"fx-tab\" role=\"tab\" data-fx-tab=\"2\"\u003eSpecifications\u003c\/button\u003e \u003cbutton class=\"fx-tab\" role=\"tab\" data-fx-tab=\"3\"\u003eDocuments\u003c\/button\u003e \u003cbutton class=\"fx-tab\" role=\"tab\" data-fx-tab=\"4\"\u003eShipping Information\u003c\/button\u003e \u003cbutton class=\"fx-tab\" role=\"tab\" data-fx-tab=\"5\"\u003eWhy Buy From Ai-Paipai?\u003c\/button\u003e \u003c\/div\u003e \u003cdiv class=\"fx-panel is-active\" data-fx-panel=\"0\"\u003e \u003cdiv style=\"border:2px solid #2b6cb0;background:#f0f7ff;padding:14px 18px;margin:0 0 18px;border-radius:8px;\"\u003e \u003ch3 style=\"margin:0 0 6px;color:#2b6cb0;\"\u003e✅ Authorized Distributor — Ai-Paipai (Shenzhen AiPaipai Intelligent Technology Co., Ltd.)\u003c\/h3\u003e \u003cp style=\"margin:0;font-size:14px;\"\u003eThis product is supplied by an \u003cb\u003eauthorized distributor\u003c\/b\u003e of the original brand.\nWe provide \u003cb\u003elocal technical support, pre-installed SDK \/ mirror images, and OEM \/ ODM customization\u003c\/b\u003e, plus fast global shipping.\u003c\/p\u003e \u003c\/div\u003e \u003cp\u003eAIBOX-OrinNano is equipped with NVIDIA's original Jetson Orin Nano core module (8GB RAM version), providing up to 67 TOPS of computing power, supporting private deployment of mainstream AI models such as Transformer and ROS robot models, thereby realizing larger and more complex deep neural networks, and realizing visual development tasks such as object recognition, target detection and tracking, and speech recognition, meeting higher-level AI application scenario requirements.\u003c\/p\u003e \u003cul\u003e \u003cli style=\"font-weight: bold;\"\u003e\u003cstrong\u003eProduct Datasheet: \u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0592\/4965\/5892\/files\/AIBOX-OrinNano_AIBOX-OrinNX_Specification_EN.pdf?v=1749620262\"\u003eClick Here\u003c\/a\u003e\u003c\/strong\u003e\u003c\/li\u003e \u003cli style=\"font-weight: bold;\"\u003e\u003cstrong\u003eProduct Wiki: \u003ca href=\"https:\/\/wiki.t-firefly.com\/en\/AIBOX-Orin-Nano\/index.html\"\u003eClick Here\u003c\/a\u003e\u003c\/strong\u003e\u003c\/li\u003e \u003c\/ul\u003e \u003ch2 style=\"font-size: 20px;\"\u003e\u003cstrong\u003eApplication Cases \u003c\/strong\u003e\u003c\/h2\u003e \u003cul\u003e \u003cli style=\"font-weight: bold;\"\u003e\u003ca href=\"https:\/\/www.firefly.store\/blogs\/technical-case\/aibox-application-case-background-removal-via-u-net\"\u003e\u003cstrong\u003eBackground Removal via U²-Net\u003c\/strong\u003e\u003c\/a\u003e\u003c\/li\u003e \u003cli style=\"font-weight: bold;\"\u003e\u003cstrong\u003e\u003ca href=\"https:\/\/www.firefly.store\/blogs\/news\/monocular-depth-estimation-aibox-application\"\u003eMonocular Depth Estimation\u003c\/a\u003e\u003c\/strong\u003e\u003c\/li\u003e \u003c\/ul\u003e \u003ch2 style=\"font-size: 20px;\"\u003e\u003cstrong\u003eFeature\u003c\/strong\u003e\u003c\/h2\u003e \u003cul\u003e \u003cli\u003e \u003cstrong\u003eHigh-performance Edge Computing Module: \u003c\/strong\u003eThe NVIDIA Jetson Orin Nano edge computing module (8GB version) is equipped with a six-core ARM CPU and a 1024-core NVIDIA Ampere architecture GPU (including 32 Tensor Cores), which can run multiple AI application pipelines simultaneously and provide powerful inference performance.\u003cstrong\u003e\u003cbr\u003e\u003c\/strong\u003e \u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eMultiple Deep Learning Frameworks: \u003c\/strong\u003eIt supports a variety of cuDNN-accelerated deep learning frameworks, including PaddlePaddle, PyTorch, TensorFlow, MATLAB, MxNet, Caffe2, Chainer, Keras, etc., as well as custom operator development, and supports Docker containerization technology.\u003cbr\u003e \u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eAluminum Alloy Enclosure With Efficient Heat Dissipation: \u003c\/strong\u003eAIBOX adopts an industrial-grade all-metal shell and an aluminum alloy structure with good thermal conductivity. The grille design on the side of the top cover is conducive to external airflow and efficient heat dissipation, ensuring computing performance and stability even in high-temperature operating environments.\u003c\/li\u003e \u003c\/ul\u003e \u003ch2 style=\"font-size: 20px;\"\u003e\u003cstrong\u003eApplication\u003c\/strong\u003e\u003c\/h2\u003e \u003cul\u003e \u003cli\u003e \u003cstrong\u003eAI Software Stack And Ecosystem:\u003c\/strong\u003e NVIDIA JetPack, Isaac ROS, and reference AI workflows seamlessly integrate cutting-edge technologies into your products without expensive in-house AI resources. Experience end-to-end acceleration of AI applications and get to market faster using the same powerful technology that drives data center and cloud deployments.\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eThe Private Deployment Of Large Models:\u003c\/strong\u003e Large language model: supports the Ollamalocal large model deployment framework and private deployment of ultra-large-scale parameterized models: Llama3, Phi-3 Mini. Vision model: supports EfficientVIT, NanoOWL, NanoSAM, SAM, TAM. AI painting: supports ComfyUIgraphical deployment framework and private deployment of Flux, and a stable Diffusion image generation model in the AIGC field.\u003cbr\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003ch2 style=\"font-size: 20px;\"\u003e\u003cstrong\u003eHardware Overview\u003c\/strong\u003e\u003c\/h2\u003e \u003cp\u003e\u003cstrong\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0592\/4965\/5892\/files\/ORINAIBOX.webp?v=1751269631\"\u003e\u003c\/strong\u003e\u003c\/p\u003e \u003chr\u003e \u003ch2\u003e \u003c\/h2\u003e \u003c\/div\u003e \u003cdiv class=\"fx-panel\" data-fx-panel=\"1\"\u003e \u003ch3\u003eShipping list\u003c\/h3\u003e \u003cul\u003e \u003cli\u003eMain unit × 1\u003c\/li\u003e \u003cli\u003ePower adapter \/ cable (region plug on request) × 1\u003c\/li\u003e \u003cli\u003eAccessories vary by configuration — contact us for the exact included list.\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003cdiv class=\"fx-panel\" data-fx-panel=\"2\"\u003e \u003cdiv class=\"fx-specs\"\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eShipping list\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eAIBOX-OrinNano*1\n12V3A Power Adapter*1\nType-C 2.0 USB Cable*1\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eAi performance\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e67 TOPS\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eTraditional network architectures\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eTraditional network architectures such as CNN, RNN, and LSTM; a variety of deep learning frameworks include TensorFlow, PyTorch, MXNet, PaddlePaddle, ONNX, and Darknet; custom operator development.\nDocker container management technology facilitates easy image deployment.\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eAi software stack\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eNVIDIA Jetson Orin offers unparalleled AI computing, large unified memory, and comprehensive software stacks, delivering superior energy efficiency to drive the latest generative AI applications. It’s capable of fast inference for any generative AI models powered by the transformer architecture, providing superior edge performance on MLPerf.\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eLarge model\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eRobotic models: ROS models.\nLarge language models: The private deployment of ultra-large-scale parameter models under the Transformer architecture, such as LLaMa2, ChatGLM, and Qwen.\nVision models: ViT, Grounding DINO, and SAM.\nAI painting: Stable Diffusion V1.5 image generation model in the AIGC field.\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eCpu\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eHexa-core 64-bit ARM Cortex-A78AE v8.2 processor, up to 1.7GHz\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003ePower\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eDC 12V (DC 5.5 x 2.1mm) \u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003ePower consumption\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eNormal: 7.2W (12V\/600mA)\nMax: 18W (12V\/1500mA)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eVideo output\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e1×HDMI 2.1 (4K@60fps)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eOs\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eThe Jetson system, based on Ubuntu 22.04, offers a comprehensive desktop Linux environment with accelerated graphics, supporting libraries such as NVIDIA CUDA, TensorRT, and CuDNN.\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eDimension\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e93.4 mm x 93.4 mm x 50 mm\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eWeight\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e≈ 500g\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eEnvironment\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eOperating temperature: -20℃~60℃\nStorage temperature: -20℃~70℃\nStorage Humidity: 10%~90%RH (non-condensing)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eWatchdog\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eSupport external watchdog\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eEthernet\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e1 × Gigabit Ethernet (1000Mbps \/ RJ45)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eUsb\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e2 × USB 3.0 (Max: 1A)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eOther\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e1 × Type-C (USB 2.0 OTG)\n1 × Console (debug serial port)\n1 × Recovery\n1 × power button\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eProduct tutorials\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eClick Here\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eSdk software and firmware files\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eClick Here\u003c\/div\u003e \u003c\/div\u003e \u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-panel\" data-fx-panel=\"3\"\u003e \u003cdiv class=\"fx-docs\"\u003e \u003cdiv class=\"fx-doc\"\u003e \u003cspan\u003eProduct tutorials\u003c\/span\u003e\u003ca href=\"#\" target=\"_blank\" rel=\"noopener\"\u003eClick Here\u003c\/a\u003e \u003c\/div\u003e \u003cdiv class=\"fx-doc\"\u003e \u003cspan\u003eProduct datasheet\u003c\/span\u003e\u003ca href=\"#\" target=\"_blank\" rel=\"noopener\"\u003eClick Here\u003c\/a\u003e \u003c\/div\u003e \u003cdiv class=\"fx-doc\"\u003e \u003cspan\u003eSDK software and firmware files\u003c\/span\u003e\u003ca href=\"#\" target=\"_blank\" rel=\"noopener\"\u003eClick Here\u003c\/a\u003e \u003c\/div\u003e \u003c\/div\u003e \u003cp class=\"fx-note\"\u003eDocument links will be replaced with the official Firefly resource URLs on request.\u003c\/p\u003e \u003c\/div\u003e \u003cdiv class=\"fx-panel\" data-fx-panel=\"4\"\u003e \u003cp\u003e\u003cb\u003eOur cooperating carriers:\u003c\/b\u003e FedEx, DHL, UPS, SF Express\u003c\/p\u003e \u003ch3\u003eDelivery Area And Cost\u003c\/h3\u003e \u003cdiv class=\"fx-scroll\"\u003e \u003ctable class=\"fx-table\"\u003e \u003cthead\u003e\u003ctr\u003e \u003cth\u003eCountry\/Region\u003c\/th\u003e \u003cth\u003e0–2kg\u003c\/th\u003e \u003cth\u003e2–3kg\u003c\/th\u003e \u003cth\u003e3–4kg\u003c\/th\u003e \u003cth\u003e4–5kg\u003c\/th\u003e \u003cth\u003e5–6kg\u003c\/th\u003e \u003cth\u003e6–7kg\u003c\/th\u003e \u003cth\u003e7–8kg\u003c\/th\u003e \u003cth\u003e8–9kg\u003c\/th\u003e \u003cth\u003e9–10kg\u003c\/th\u003e \u003c\/tr\u003e\u003c\/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd\u003eJapan, Taiwan, Hong Kong, Macau\u003c\/td\u003e \u003ctd\u003e$15\u003c\/td\u003e \u003ctd\u003e$20\u003c\/td\u003e \u003ctd\u003e$25\u003c\/td\u003e \u003ctd\u003e$30\u003c\/td\u003e \u003ctd\u003e$35\u003c\/td\u003e \u003ctd\u003e$40\u003c\/td\u003e \u003ctd\u003e$45\u003c\/td\u003e \u003ctd\u003e$50\u003c\/td\u003e \u003ctd\u003e$55\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd\u003eSingapore, Thailand, Malaysia\u003c\/td\u003e \u003ctd\u003e$20\u003c\/td\u003e \u003ctd\u003e$25\u003c\/td\u003e \u003ctd\u003e$30\u003c\/td\u003e \u003ctd\u003e$35\u003c\/td\u003e \u003ctd\u003e$40\u003c\/td\u003e \u003ctd\u003e$45\u003c\/td\u003e \u003ctd\u003e$50\u003c\/td\u003e \u003ctd\u003e$55\u003c\/td\u003e \u003ctd\u003e$60\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd\u003eIndonesia, Philippines\u003c\/td\u003e \u003ctd\u003e$25\u003c\/td\u003e \u003ctd\u003e$30\u003c\/td\u003e \u003ctd\u003e$40\u003c\/td\u003e \u003ctd\u003e$50\u003c\/td\u003e \u003ctd\u003e$60\u003c\/td\u003e \u003ctd\u003e$70\u003c\/td\u003e \u003ctd\u003e$80\u003c\/td\u003e \u003ctd\u003e$85\u003c\/td\u003e \u003ctd\u003e$95\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd\u003eSouth Korea\u003c\/td\u003e \u003ctd\u003e$25\u003c\/td\u003e \u003ctd\u003e$35\u003c\/td\u003e \u003ctd\u003e$35\u003c\/td\u003e \u003ctd\u003e$45\u003c\/td\u003e \u003ctd\u003e$45\u003c\/td\u003e \u003ctd\u003e$55\u003c\/td\u003e \u003ctd\u003e$55\u003c\/td\u003e \u003ctd\u003e$65\u003c\/td\u003e \u003ctd\u003e$65\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd\u003eUnited States, Australia, New Zealand, Canada, UK, and most of Western Europe\u003c\/td\u003e \u003ctd\u003e$30\u003c\/td\u003e \u003ctd\u003e$45\u003c\/td\u003e \u003ctd\u003e$55\u003c\/td\u003e \u003ctd\u003e$65\u003c\/td\u003e \u003ctd\u003e$75\u003c\/td\u003e \u003ctd\u003e$85\u003c\/td\u003e \u003ctd\u003e$95\u003c\/td\u003e \u003ctd\u003e$105\u003c\/td\u003e \u003ctd\u003e$115\u003c\/td\u003e \u003c\/tr\u003e \u003ctr\u003e \u003ctd\u003eOther regions (Eastern Europe, Middle East, Latin America, etc.)\u003c\/td\u003e \u003ctd\u003e$50\u003c\/td\u003e \u003ctd\u003e$65\u003c\/td\u003e \u003ctd\u003e$80\u003c\/td\u003e \u003ctd\u003e$95\u003c\/td\u003e \u003ctd\u003e$110\u003c\/td\u003e \u003ctd\u003e$125\u003c\/td\u003e \u003ctd\u003e$135\u003c\/td\u003e \u003ctd\u003e$150\u003c\/td\u003e \u003ctd\u003e$165\u003c\/td\u003e \u003c\/tr\u003e \u003c\/tbody\u003e \u003c\/table\u003e \u003c\/div\u003e \u003cp class=\"fx-note\"\u003eShipping time is for reference only; the actual situation shall prevail.\u003c\/p\u003e \u003c\/div\u003e \u003cdiv class=\"fx-panel\" data-fx-panel=\"5\"\u003e\n Why Buy From Ai-Paipai? \u003cul\u003e \u003cli\u003e \u003cb\u003eAuthorized \u0026amp; Genuine\u003c\/b\u003e — sourced directly from brand-approved channels.\u003c\/li\u003e \u003cli\u003e \u003cb\u003eLocal Engineering Support\u003c\/b\u003e — datasheets, SDKs, and pre-flashed images in English and Chinese.\u003c\/li\u003e \u003cli\u003e \u003cb\u003eOEM \/ ODM \u0026amp; FPGA Customization\u003c\/b\u003e — tailor specs, enclosures, and BSP for your project.\u003c\/li\u003e \u003cli\u003e \u003cb\u003eOne-Stop Sourcing\u003c\/b\u003e — Firefly + youyeetoo + our own FPGA \/ edge lineup in one store.\u003c\/li\u003e \u003c\/ul\u003e \u003c\/div\u003e \u003c\/div\u003e \u003cstyle\u003e.fx-tabs{margin:24px 0;border:1px solid #e5e7eb;border-radius:10px;overflow:hidden;background:#fff}.fx-tablist{display:flex;flex-wrap:wrap;gap:0;border-bottom:1px solid #e5e7eb;background:#f8fafc}.fx-tab{flex:1 1 auto;min-width:120px;padding:14px 16px;border:0;background:transparent;cursor:pointer;font:600 14px\/1.3 inherit;color:#475569;border-bottom:3px solid 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