# Google Coral Dev Board Mini

**Type:** Product page · **SKU:** TPH-104063 · **Brand:** [The Pi Hut](https://core-electronics.com.au/brands/the-pi-hut)
**Page:** https://core-electronics.com.au/google-coral-dev-board-mini-machine-learning.html ([markdown](https://core-electronics.com.au/google-coral-dev-board-mini-machine-learning.html.md))

A development board to quickly prototype on-device ML products. The Google Coral Dev Board Mini is a single-board computer that provides fast machine...

## Pricing

- **Price:** $294.95 (inc GST) — $268.14 AUD, exc GST
- **Quantity discounts:** 3+ $257.41 (exc GST) · 5+ $249.36 (exc GST)

## Availability & dispatch

- Available with a lead time — expect dispatch between Sep 02 and Sep 07.

## Description

**A development board to quickly prototype on-device ML products.**

The Google Coral Dev Board Mini is a single-board computer that provides fast machine learning (ML) inferencing in a small form factor. It's primarily designed as an evaluation device for theAccelerator Module(a surface-mounted module that provides the Edge TPU), but it's also a fully-functional embedded system you can use for various on-device ML projects.

[A camera module designed specifically for the Google Coral range is available here.](https://core-electronics.com.au/products/google-coral-camera)

### Performs high-speed ML inferencing[](https://coral.ai/products/dev-board-mini#performs-high-speed-ml-inferencing)

The on-board Edge TPU coprocessor is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt). For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 FPS, in a power efficient manner.[See more performance benchmarks](https://coral.ai/docs/edgetpu/benchmarks/).

### Provides a complete system[](https://coral.ai/products/dev-board-mini#provides-a-complete-system)

A single-board computer with SoC + ML + wireless connectivity, all on the board running a derivative of Debian Linux we call Mendel, so you can run your favorite Linux tools with this board.

### Supports TensorFlow Lite[](https://coral.ai/products/dev-board-mini#supports-tensorflow-lite)

No need to build models from the ground up.[TensorFlow Lite](https://www.tensorflow.org/lite)models can be compiled to run on the Edge TPU.

### Supports AutoML Vision Edge[](https://coral.ai/products/dev-board-mini#supports-automl-vision-edge)

Easily build and deploy fast, high-accuracy custom image classification models to your device with[AutoML Vision Edge](https://cloud.google.com/vision/automl/docs/edge-quickstart).

Specifications| CPU | MediaTek 8167s SoC (Quad-core Arm Cortex-A35) |
|---|---|
| GPU | IMG PowerVR GE8300 (integrated in SoC) |
| ML accelerator | Google Edge TPU coprocessor: 4 TOPS (int8); 2 TOPS per watt |
| RAM | 2 GB LPDDR3 |
| Flash memory | 8 GB eMMC |
| Wireless | Wi-Fi 5 (802.11a/b/g/n/ac); Bluetooth 5.0 |
| Audio/video | 3.5mm audio jack; digital PDM microphone; 2.54mm 2-pin speaker terminal; micro HDMI (1.4); 24-pin FFC connector for MIPI-CSI2 camera (4-lane); 24-pin FFC connector for MIPI-DSI display (4-lane) |
| Input/output | 40-pin GPIO header; 2x USB Type-C (USB 2.0) |

Resources### Datasheet[](https://coral.ai/products/dev-board-mini#datasheet)

- [Dev Board Mini datasheet](https://coral.ai/docs/dev-board-mini/datasheet/)

### Schematics[](https://coral.ai/products/dev-board-mini#schematics)

- [Dev Board Mini schematics and layout](https://github.com/google-coral/electricals/tree/master/dev_board_mini)

### Application notes[](https://coral.ai/products/dev-board-mini#application-notes)

- [Get started with the Dev Board Mini](https://coral.ai/docs/dev-board-mini/get-started/)
- [Connect to the Dev Board Mini I/O pins](https://coral.ai/docs/dev-board-mini/gpio/)
- [Connect a camera to the Dev Board Mini](https://coral.ai/docs/dev-board-mini/camera/)
- [Connect to the Dev Board Mini's serial console](https://coral.ai/docs/dev-board-mini/serial-console/)
- [Update or flash the Dev Board Mini](https://coral.ai/docs/dev-board-mini/reflash/)

### Software guides[](https://coral.ai/products/dev-board-mini#software-guides)

- [Model compatibility on the Edge TPU](https://coral.ai/docs/edgetpu/models-intro)
- [Edge TPU inferencing overview](https://coral.ai/docs/edgetpu/inference/)
- [Run multiple models with multiple Edge TPUs](https://coral.ai/docs/edgetpu/multiple-edgetpu/)
- [Pipeline a model with multiple Edge TPUs](https://coral.ai/docs/edgetpu/pipeline/)

### API references[](https://coral.ai/products/dev-board-mini#api-references)

- [PyCoral API (Python)](https://coral.ai/docs/reference/py/)
- [Libcoral API (C++)](https://coral.ai/docs/reference/cpp/)
- [Libedgetpu API (C++)](https://coral.ai/docs/reference/cpp/edgetpu/)

### Downloads[](https://coral.ai/products/dev-board-mini#downloads)

- [Edge TPU compiler](https://coral.ai/docs/edgetpu/compiler)
- [Pre-compiled models](https://coral.ai/models/)
- [All software downloads](https://coral.ai/software)

## Images

- [Product image 1](https://core-electronics.com.au/media/catalog/product/T/P/TPH-104063-1.jpg)