{"title":"DX-M1 AI Accelerator M.2 Module - 4GB LPDDR5, 25 TOPS","handle":"dx-m1-ai-accelerator-m-2-module-with-4gb-lpddr5-25-tops","url":"/products/dx-m1-ai-accelerator-m-2-module-with-4gb-lpddr5-25-tops","description":"Add dedicated edge AI acceleration to your host system with this compact DX-M1 M.2 module. It delivers 25 TOPS (INT8) inference performance in a standard M.2 2280 form factor, with low 2W–5W power consumption for embedded and mobile systems.The module uses an M.2 M-Key interface over PCIe Gen3 x4, with compatibility for x1 mode, making it suitable for x86 PCs, LattePanda boards, Raspberry Pi 5 setups via suitable HATs, and other x86/ARM platforms. Onboard 4GB LPDDR5 memory helps handle larger models, while 1Tbit QSPI NAND Flash is included for firmware storage.Development is supported by the DXNN® SDK, which provides a workflow for model compilation, optimisation and runtime deployment. It supports common AI frameworks including PyTorch, ONNX, TensorFlow, TensorFlow Lite, Keras and XGBoost for applications such as robotics, visual SLAM, real-time video analytics, object detection and industrial inspection.Included in the package is one DX-M1 AI Accelerator M.2 Module with 4GB LPDDR5.Features:Edge inference: 25 TOPS (INT8) performance for complex neural networks and multi-stream video analysis.Low power operation: Designed to operate within a 2W-5W power envelope.M.2 integration: Standard M.2 M-Key (2280) format for broad platform compatibility.PCIe interface: Uses PCIe Gen3 x4 and is backward compatible with x1 mode.Development support: Backed by the DXNN® SDK for compilation, optimisation and runtime execution.Framework support: Supports PyTorch, TensorFlow, TensorFlow Lite, Keras and XGBoost, with ONNX workflow support.Industrial use: Suitable for robotics, visual SLAM, AI visual inspection, safety monitoring and autonomous systems.Specifications:Processor Performance: 25 TOPS (INT8)Interface: M.2 M-Key, PCI Express Gen3 x4 (compatible with x1 mode)Memory: 4GB LPDDR5, 1Tbit QSPI NAND FlashPower Consumption: 2W ~ 5WPower Range: 3.3V±5%Framework Support: PyTorch, ONNX, TensorFlow, TensorFlow Lite, Keras, XGBoostOperating Systems: Windows 10/11, Ubuntu 20.04/22.04 LTSOperating Temperature: -25°C ~ 85°C (Throttling); 25°C ~ 65°C (Non_ Throttling)Product Dimensions: 22 mm x 80 mm x 4.1 mm/0.87 inch x 3.15 inch x 0.16 inchA strong fit for makers and engineers adding local AI inference to robotics, embedded vision, industrial automation or edge computing builds.","vendor":"DFRobot","product_type":"AI Accelerator Module","in_stock":true,"options":[],"variants":[{"id":15662,"title":"Default Title","sku":"DF-DFR1252","mpn":"DFR1252","price":341.75,"on_sale":false,"in_stock":true,"available_quantity":112}]}