{"product_id":"aibox-8550-qcs8550-embedded-mini-pc","title":"AIBOX-8550 QCS8550 Embedded Mini 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-8550 QCS8550 Embedded Mini PC\u003c\/strong\u003e is a Firefly product sold by Ai-Paipai. Key specifications — Soc: Qualcomm QCS8550 · Npu: Dual eNPU V3: Equipped with 4 HVX (Hexagon Vector… · Ram: 16GB LPDDR5x · Storage: 256GB UFS4.0 · Ethernet: 2 × Gigabit Ethernet (1000Mbps\/RJ45). Typical applications: edge AI inference 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\u003eThe AIBOX-8550 is equipped with a Qualcomm QCS8550 octa-core AI processor, integrating a 48 TOPS NPU, supporting mainstream AI large language models and deep learning frameworks. It features a built-in Adreno 740 GPU, supporting ray tracing and 8K video codecs. Utilizing an industrial-grade all-metal casing, it offers efficient heat dissipation, ensuring stable operation around the clock and meeting the demands of demanding industrial applications.\u003c\/p\u003e \u003cul\u003e \u003cli style=\"font-weight: bold;\"\u003e\u003cstrong\u003eProduct Datasheet: \u003ca href=\"https:\/\/download.t-firefly.com\/Spec\/Computers\/AIBOX-8550_Specification_EN.pdf\" target=\"_blank\" rel=\"noopener\"\u003eClick Here\u003c\/a\u003e\u003c\/strong\u003e\u003c\/li\u003e \u003c\/ul\u003e \u003ch2 style=\"font-size: 23px;\"\u003e\u003cstrong\u003eFeature\u003c\/strong\u003e\u003c\/h2\u003e \u003cul\u003e \u003cli\u003e \u003cstrong\u003eHigh-Performance Processor Qualcomm QCS8550:\u003c\/strong\u003e The QCS8550 features an eight-core Kryo CPU based on the ARM architecture, with a clock speed of up to 3.36 GHz, providing powerful support for high-performance computing and multitasking.\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eDeployment of Large AI Models: \u003c\/strong\u003eSupports the private deployment of large-scale Transformer models (including Qwen, Llama, Gemma, DeepSeek-R1, and Phi series), as well as mainstream deep learning frameworks such as TensorFlow, PyTorch, Caffe, and ONNX.\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eSupports Ray Tracing Technology:\u003c\/strong\u003e Features an Adreno 740 GPU, providing full ray tracing support and compatibility with OpenGL ES 3.2, Vulkan 1.2, and OpenCL 3.0. Combined with Adreno Neural Processing technology, it significantly enhances graphics and AI computing performance.\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003e8K Video Encoding and Decoding:\u003c\/strong\u003e Advanced video processing supporting 8K@60fps\/4K@240fps decoding and 8K@30fps\/4K@120fps encoding.\u003c\/li\u003e \u003c\/ul\u003e \u003ch2 style=\"font-size: 23px;\"\u003e\u003cstrong\u003eProduct Overview\u003c\/strong\u003e\u003c\/h2\u003e \u003cp\u003e\u003cstrong\u003e\u003cimg style=\"display: block; margin-left: auto; margin-right: auto;\" alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0592\/4965\/5892\/files\/ScreenShot_2025-12-03_162506_694.webp?v=1764750475\"\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\"\u003eSoc\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eQualcomm QCS8550\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eCpu\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eQualcomm Kryo® CPU: Octa-core 64-bit (1×GoldPlus@3.2GHz + (2+2)Gold@2.8GHz + 3×Silver@2.0GHz), 4nm advanced process, maximum frequency up to 3.36GHz\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eGpu\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eAdreno 740 GPU: Supports ray tracing technology, OpenGL ES 3.2, Vulkan 1.2, full-profile OpenCL 3.0, and Adreno NN Direct\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eNpu\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eDual eNPU V3: Equipped with 4 HVX (Hexagon Vector Extensions), 1 HMX (Hexagon Matrix Extension); Computing power up to 48 TOPS (INT8), 12 TOPS (FP16)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eRam\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e16GB LPDDR5x\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eStorage\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e256GB UFS4.0\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\/5A (5.5 × 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: 4.32W(12V\/360mA), Max: 20W(12V\/1670mA), Min(Sleep): 0.6W(12V\/50mA)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eOs\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eUbubtu\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eSoftware support\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003eSupports on-premises deployment of large-scale parameter models based on the Transformer architecture, such as large language models (LLMs) including the Deepseek-R1 series, Gemma series, Llama series, Qwen series, Phi series, etc.\nSupports the QNN AI inference framework, as well as various deep learning frameworks including TensorFlow, TensorFlow Lite, PyTorch, ONNX, etc.\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eDimension\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e93.4mm × 93.4mm × 50.0mm\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℃, Storage Temperature: -20℃~70℃, Operating Humidity: 10%~90%RH (No condensation)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eEthernet\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e2 × 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 × USB3.0 (Max: 1A), 1 × Type-C (For download)\u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"fx-spec\"\u003e \u003cdiv class=\"fx-k\"\u003eButton\u003c\/div\u003e \u003cdiv class=\"fx-v\"\u003e1 × Power, 1 × Recovery\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 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(function () {\n var roots = document.querySelectorAll('[data-fx-tabs]');\n roots.forEach(function (root) {\n var tabs = root.querySelectorAll('[data-fx-tab]');\n var panels = root.querySelectorAll('[data-fx-panel]');\n tabs.forEach(function (t) {\n t.addEventListener('click', function () {\n var i = t.getAttribute('data-fx-tab');\n tabs.forEach(function (x) { x.classList.toggle('is-active', x === t); });\n panels.forEach(function (p) { p.classList.toggle('is-active', p.getAttribute('data-fx-panel') === i); });\n });\n });\n });\n })(); \u003c\/script\u003e","brand":"Firefly","offers":[{"title":"16G RAM+256G ROM","offer_id":48422469173506,"sku":"firefly-aibox-8550-qcs8550-embedded-mini-pc-42730903175252","price":799.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0837\/5953\/0242\/files\/8550_3e3a0150-8847-4590-aacf-9bf14ff58084.webp?v=1788244310","url":"https:\/\/ai-paipai.store\/products\/aibox-8550-qcs8550-embedded-mini-pc","provider":"Ai-Paipai","version":"1.0","type":"link"}