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 100+ FPS, in a power efficient manner. See more performance benchmarks.
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
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.
Scale from prototype to production
Considers your manufacturing needs. The SoM can be removed from the baseboard, ordered in bulk, and integrated into your hardware.
|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|
|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||3.3V power rail; 40 - 255 ohms programmable impedance; ~82 mA max current|
|Power||5V DC (USB Type-C)|
|Dimensions||88 mm x 60 mm x 24mm|