Neural Network Module


Product Overview

The Bitmain Sophon Neural Network Module (NNM) is a USB module that designed for Deep Learning inference on various edge application. NNM is powered by high performance, low power Sophon BM1880 chip. BM1880 chip supports DNN/CNN/RNN/LSTM models or uniquely trained networks, and can perform facial detection, recognition, facial expression analysis, object detection, recognition, vehicle license plate recognition, voiceprint recognition, etc. The NNM enables traditional product with AI functions, and can be used in smart IPC, Robots, industrial PC, etc.

Product Features

  • Power and all data provided over USB 9pin (pin width: 1.25mm) interface

  • Supports DNN/CNN/RNN/LSTM models profiling, compiling and tuning

  • Real-time inference in edge device Quickly deploy existing

  • DNN/CNN/RNN/LSTM models or uniquely trained networks Features

  • Sophon BM1880 with energy efficient DNN/CNN/RNN/LSTM processing

Target AI Functions

  • Facial detection (Frame by Frame), recognition and expression analysis, such as Age, Gender, etc.

  • Human attributes and pose analysis

  • Object detection and recognition

  • Vehicle license plate recognition

  • Voice print recognition

Product Technical Specification


Sophon BM1880

Supported Framework

Caffe, ONNX, Tensorflow, Pytorch

Supported AI Models

ResNet50, Yolo V2, GoogleNet V1, MobileNet v1&v2, SSD300, AlexNet, VGG16

H.264 decoder, MJPEG encoder/decoder

1x 1080p @60fps or 2x 1080p @30fps H.264 decoder, 75fps for FHD images


USB 9pin (pin width: 1.25mm) interface


38*38 mm

Operating environmental temperature

0 – 40C (commercial level)

Hot plugin/plugoff




Minimum system requirement

X86_64 computer running Windows or Ubuntu USB3.0 or USB2.0 port


  • BMNet: Bitmain Compiler which can convert supported AI models to internal format accelerated by Sophon TPU.

  • ONNX: Compiler which can convert ONNX format to internal format accelerated by Sophon TPU.

  • Quantization Tool: Convert FP32 to INT8 and support calibration function.

Please connect the UART cable to module as below: