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Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS
Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS
Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS
Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS
Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS

Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS

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Product Code: DBHO-063

MPN #: S164

If you want to run AI models on a Raspberry Pi 5, the lack of processing power is a big roadblock. Slow inference makes real-time vision, voice, or sensor tasks feel laggy and can waste battery life. The Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS adds a powerful AI accelerator that removes that bottleneck, letting you run complex models quickly and efficiently.

 

Sixfab Edge AI Expansion Board for Raspberry Pi 5 with DX-M1 M.2 Module, 25 TOPS with Sixfab

Turn your Pi into a smart edge device in minutes. This board plugs into the Raspberry Pi 5 and carries a DEEPX DX-M1 accelerator that delivers 25 TOPS of INT8 performance. It is built for makers, developers, and hobbyists who need fast AI without buying a separate server. Without this board, you would have to limit your models or wait for cloud processing, which adds latency and cost. Sixfab gives you a compact, plug-and-play solution that fits on the Pis footprint.

 

 

Key Features

 

    • DEEPX DX-M1 AI accelerator with 25 TOPS INT8 performance.
    • 4 GB LPDDR5 memory on the module for rapid data handling.
    • PCIe Gen 2/3 1 host interface via 40 mm FFC cable.
    • Three M.2 slots: AI M-Key, NVMe M-Key, LTE/5G Key-B.
    • NVMe storage support up to 2280 size with high read/write speeds.
    • Cellular slot with nano-SIM and eUICC for remote connectivity.
    • USB-C Power Delivery, 27 W minimum, 45 W recommended.
    • Pi back-power pins deliver 5 V and 3 A per pin.



Specifications
AI Accelerator  
AI Accelerator DEEPX DX-M1, 25 TOPS at INT8, on swappable M.2 module
NPU Memory 4 GB LPDDR5 @ 5600 MT/s on DX-M1 module
Host Interface  
Host Interface PCIe Gen 2/3 ×1 over 40 mm FFC cable
Expansion  
M.2 Slots 3 × M.2, AI M-Key, NVMe M-Key, LTE/5G Key-B
NVMe Storage 2230/2242/2260/2280, 380–440 MB/s read, 350–410 MB/s write
Cellular M.2 Key-B, 1 × nano SIM, eUICC supported
Power  
Power Input USB-C PD, 27 W minimum, 45 W recommended
Pi Back-Power 2 × 5V + 2 × GND pogo pins, 3 A per pin
Mechanical  
Form Factor 88.46 × 89.19 mm, ~36.26 mm Z-stack with Raspberry Pi 5
Environmental  
Operating Temperature 0–70 °C (Commercial)
Compatibility  
Supported Host Raspberry Pi 5
Host OS Raspberry Pi OS (Trixie)
Software  
Runtime dxrt-runtime, APT install, Python & C++ APIs
Model Pipeline ONNX → DXNN via DX-COM compiler
Installation  
Hot-plug Not supported. Power off Raspberry Pi 5 before mounting

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