· High-Performance AI Processor IQ-9075
· GPU/VPU Graphics & Multimedia Processing
· Up to 36GB LPDDR5 Memory
· All-Scenario Multi-Standard Network Connectivity
· 8-Channel GMSL2 Vision Capture Interface
· Support -40°C to 85°C Wide Temperature
· Rich Industrial Expansion Interfaces
· Full-Stack Software Ecosystem Support
AI Large Model
Ubuntu
Yocto
RTOS
Powered by Qualcomm IQ-9075 processor, delivering up to 200 TOPS of peak AI computing power and achieving 12TPS large model inference, enabling on-device private deployment of large language models. Its octa-core CPU runs at up to 2.36GHz, well-suited for high‑load edge AI and multi‑task concurrency. It features built‑in security subsystem and four real‑time cores. Leveraging Qualcomm Linux software stack, it supports Ubuntu/Yocto systems and mainstream AI inference frameworks. With an industrial wide‑temperature design, it comes standard with GMSL2, CAN‑FD, RS485, and opto‑isolated I/O.
AI Processor IQ-9075
Powerful GPU & 8K Codec VPU
Up to 36GB LPDDR5 Memory
Multi-Standard Network Connectivity
8 x GMSL2 HD Vision Inputs
-40°C~85°C Wide Temperature
Industrial Expansion Interfaces
Full-Stack Software Ecosystem
Powered by Qualcomm IQ-9075 processor, featuring dual Hexagon NPUs with peak sparse INT8 computing power of up to 200 TOPS. It supports CPU/GPU/NPU hardware‑accelerated collaboration, enabling on‑device private deployment of large language models and generative AI, delivering LLM inference performance of up to 12TPS@13B. It efficiently handles a wide range of complex AI computations and large model inference tasks.
Widely applicable in industries such as robotics, private deployment of large models, edge computing, intelligent surveillance, industrial automation and smart cities.

AIBOX-9075 |
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Basic Specifications |
SOC |
Qualcomm IQ-9075 |
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CPU |
Qualcomm Kryo® Gen6 CPU: Octa-core 64-bit (8×Kryo Gold Prime), up to 2.36 GHz |
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MCU |
Integrated subsystem with quad-core Cortex-R52 CPU; each Cortex-R52 CPU runs at up to 1.85 GHz, supporting independent boot via the OSPI interface |
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GPU |
Adreno 663 GPU supports safe GPGPU compute, up to 840MHz · Graphics APIs: Vulkan 1.2, OpenGL ES 3.2 · Compute APIs: Vulkan 1.2, OpenCL 2.0 FP, Adreno NN Direct |
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ISP |
Qualcomm Spectra 690 ISP Image Signal Processor, featuring 2× Image Front End (IFE) + 5× Lightweight Image Front End (IFE_L). Supports 24-bit HDR Bayer processing, lens distortion correction, advanced tone mapping, offset correction, lens vignetting correction, dead pixel correction, directional scaling, color lookup table, color space conversion and noise reduction. |
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NPU |
Dual Hexagon Tensor Processor integrating Qualcomm Hexagon DSP, clocked up to 1.42 GHz. It incorporates 4 Hexagon Vector Extension (HVX) and 2 Hexagon Matrix Extension (HMX) cores, delivering up to 100 TOPS (Dense INT8) / 200 TOPS (Sparse INT8), and achieves 22 token/s for Llama2-7B inference. |
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DPU |
Dual Adreno DPU1199 supports image processing features including target scaler, exclusion rectangle extraction, inline rotation, 17×17×17 3D LUT (ViG/DSPP), HDR10 enhancement, wide gamut WCG, corner rounding, and CCCS fixed-point conversion. It also supports UBWC 4.0 and DSC v1.2 image compression technologies. |
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Video codec |
Video decoding: 1×8K@60fps, 2×8K@30fps, 4×4K@60fps, 8×4K@30fps, 16×1080p@60fps, 32×1080p@30fps AV1, H.264, VP9, MPEG2 Video encoding: 2×4K@60fps, 4×4K@30fps, 8×1080p@60fps, 16×1080p@30fps H.264, HEIF/HEIC |
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RAM |
36GB LPDDR5 (ECC supported) |
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Storage |
128GB UFS2.2 |
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Storage expansion |
1 × M.2 (PCIe 4.0 x4 NVMe 2280 SSD expandable; located inside the computer) |
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Power supply |
DC 12V/5A (5.5 × 2.1mm) |
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Power consumption |
Normal: 12W(12V/1000mA), Max: 60W(12V/5000mA), Min(Sleep): 1.08W(12V/90mA) |
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OS/Software |
Ubuntu, Yocto Linux Software Stack |
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Software support |
Supports private deployment of ultra-large parameter models under the Transformer architecture, including the Deepseek-R1 series, Gemma series, Llama series, Qwen series, Phi series and other large language models. Supports private deployment of image generation models such as Stable Diffusion. Supports the QNN AI inference framework, as well as multiple deep learning frameworks including TensorFlow, TensorFlow Lite, PyTorch, ONNX, Keras and Caffe. |
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Size |
110.2mm × 102.25mm × 72.0mm (without mounting ears) |
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Environment |
Operating Temperature: -40℃ ~ 85℃, Storage Temperature: -40℃ ~ 90℃, Storage Humidity: 10% ~ 90%RH (non-condensing) |
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Interface Specifications |
Ethernet |
2 × 2.5G Ethernet (2.5Gbps/RJ45) |
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Wireless network |
Wi-Fi & Bluetooth: Supports Wi-Fi 6 and Bluetooth 5.2 (expandable via internal M.2 E-KEY) 4G/5G: Expandable via internal Mini PCIe |
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Video input |
8 × GMSL2 (2×4Pin Mini FAKRA) |
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Video output |
1 × HDMI2.0 (4K@60Hz) |
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USB |
2 × USB3.0 (Max: 1A), 1 × Type-C (Debug) |
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Antenna |
4 × 5G Antenna, 2 × Wi-Fi Antenna |
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Button |
1 × Power Button, 1 × Burn Button |
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Others |
1 × SIM Card, 1 × Phoenix terminal block (36Pin, 3.5mm pitch): 2 × RS485, 2 × CAN-FD, 12 × Opto-isolated DI/DO |
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