Description of product


The Coral USB Accelerator brings powerful ML inferencing capabilities to existing Linux systems. Featuring the Edge TPU —  a small ASIC designed and built by Google— the USB Accelerator provides high performance ML inferencing with a low power cost over a USB 3.0 interface. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 100+ fps, in a power efficient manner. This allows you to add fast ML inferencing to your embedded AI devices in a power-efficient and privacy-preserving way. Models are developed in TensorFlow Lite and then compiled to run on the USB Accelerator.
Edge TPU key benefits
  • High-speed TensorFlow Lite inferencing
  • Low power
  • Small footprint

Coral is a division of Google, that helps you build intelligent ideas with our platform for local AI.


  • Google Edge TPU ML accelerator coprocessor
  • USB 3.0 Type-C socket
  • Supports Debian Linux on host CPU
  • Models are built using TensorFlow
  • Fully supports MobileNet and Inception architectures though custom architectures are possible
  • Compatible with Google Cloud


Edge TPU ML accelerator

ASIC designed by Google that provides high performance ML inferencing for TensorFlow Lite models

Arm 32-bit Cortex-M0+ Microprocessor (MCU)

  • Up to 32 MHz max
  • 16 KB Flash memory with ECC
  •  2 KB RAM
  • USB 3.1 (gen 1) port and cable (SuperSpeed, 5Gb/s transfer speed)
  • Included cable is USB Type-C to Type-AU

Local inferencing

Run on-device ML inferencing on the Edge TPU designed by Google.

Works with Debian Linux

Connect to any Linux-based system with an included USB Type-C cable.


The Coral USB Accelerator must be connected to a host computer with the following specifications:

Any Linux computer with a USB port

  • Debian 6.0 or higher, or any derivative thereof (such as Ubuntu 10.0+)
  • System architecture of either x86_64 or ARM64 with ARMv8 instruction set

Raspberry Pi is supported

  • Only Raspberry pi <2/3 Model B/B+> 
  • While USB 3.0 provides the fastest performance Raspberry Pi only supports USB 2.0

Supported Operating Systems

  • Debian Linux
Supported Frameworks 
  • TensorFlow Lite