Provides a complete system
The Coral System-on-Module (SoM) is a fully-integrated system that helps you build embedded systems that demand
fast machine learning (ML) inferencing. It contains NXP's iMX8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM,
Wi-Fi, and Bluetooth, but its unique power comes from Google's Edge TPU coprocessor.
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 400 FPS, in a power efficient manner. This on-device processing reduces latency, increases data privacy, and removes the need for a high-bandwidth connection used to perform ML inferencing in the cloud.
Integrates with your custom hardware
The SoM connects to your own baseboard hardware with three 100-pin connectors.
Supports TensorFlow Lite
No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU.
Supports AutoML Vision Edge
Easily build and deploy fast, high-accuracy custom image classification models to your device with AutoML Vision Edge.
Also available with a baseboard as part of the Coral Dev Board.
Key benefits of the SoM:
- High-speed and low-power ML inferencing (4 TOPS @2W)
- A complete Linux system (running Mendel, a Debian derivative)
- Small footprint (40 x 48 mm)
Features:
- 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) and Bluetooth 4.2
- Dimensions: 48mm x 40mm x 5mm
Documents:
Datasheet
Getting Started Guide