Edge TPU Devices

Add accelerated ML to your embedded device

The Edge TPU is a small ASIC designed by Google that provides high performance ML inferencing for low-power devices. For example, it can concurrently execute multiple state-of-the-art vision models on high-res video at 30+ fps, in a power efficient manner.

With one of the following Edge TPU devices, you can build embedded systems with on-device AI features that are fast, secure, and power efficient.

Edge TPU Dev Board

A single-board computer with a removable Edge TPU system-on-module (SOM).

This all-in-one development board allows you to prototype embedded systems that demand fast ML inferencing. The baseboard provides all the peripheral connections you need, and the SOM board is removable so you can integrate the Edge TPU module into your own hardware.

Coming this fall. Get notified.

Edge TPU module (SOM) specifications

CPU NXP i.MX 8M SOC (quad Cortex-A53, Cortex-M4F)
GPU Integrated GC7000 Lite Graphics
ML accelerator Google Edge TPU coprocessor
RAM 1 GB LPDDR4
Flash memory 8 GB eMMC
Wireless Wi-Fi 2x2 MIMO (802.11b/g/n/ac 2.4/5GHz)
Bluetooth 4.1
Dimensions 40 mm x 48 mm

Baseboard specifications

Flash memory MicroSD slot
USB Type-C OTG
Type-C power
Type-A 3.0 host
Micro-B serial console
LAN Gigabit Ethernet port
Audio 3.5mm audio jack (CTIA compliant)
Digital PDM microphone (x2)
2.54mm 4-pin terminal for stereo speakers
Video HDMI 2.0a (full size)
39-pin FFC connector for MIPI-DSI display (4-lane)
24-pin FFC connector for MIPI-CSI2 camera (4-lane)
GPIO 40-pin expansion header
Power 5V DC (USB Type-C)
Dimensions 85 mm x 56 mm
Supported Operating Systems

Debian Linux, Android Things

Supported Frameworks

TensorFlow Lite

Edge TPU Accelerator

A USB device that adds an Edge TPU coprocessor to your system.

This small stick includes a USB Type-C socket that you can connect to any Linux-based system to perform accelerated ML inferencing. The casing includes mounting holes for attachment to host boards such as a Raspberry Pi Zero or your custom device.

Coming this fall. Get notified.

Specifications

ML accelerator Google Edge TPU coprocessor
Connector USB Type-C* (data/power)
Dimensions 65 mm x 30 mm
* Compatible with Raspberry Pi boards at USB 2.0 speeds only.
Supported Operating Systems

Debian Linux, Android Things

Supported Frameworks

TensorFlow Lite