---
product_id: 627674247
title: "Coral M.2 Accelerator with Dual Edge TPU …"
brand: "seeed studio"
price: "£0.49"
currency: GBP
in_stock: false
reviews_count: 13
url: https://www.desertcart.co.uk/products/627674247-coral-m-2-accelerator-with-dual-edge-tpu
store_origin: GB
region: United Kingdom
---

# 8 TOPS dual TPU power TensorFlow Lite & AutoML support Debian & Windows compatible Coral M.2 Accelerator with Dual Edge TPU …

**Brand:** seeed studio
**Price:** £0.49
**Availability:** ❌ Out of Stock

## Summary

> 🚀 Turbocharge your AI edge with Coral’s dual TPU powerhouse!

## Quick Answers

- **What is this?** Coral M.2 Accelerator with Dual Edge TPU … by seeed studio
- **How much does it cost?** £0.49 with free shipping
- **Is it available?** Currently out of stock
- **Where can I buy it?** [www.desertcart.co.uk](https://www.desertcart.co.uk/products/627674247-coral-m-2-accelerator-with-dual-edge-tpu)

## Best For

- seeed studio enthusiasts

## Why This Product

- Trusted seeed studio brand quality
- Free international shipping included
- Worldwide delivery with tracking
- 15-day hassle-free returns

## Key Features

- • **Compact Yet Mighty:** Sleek M.2 form factor fits right into your system, upgrading AI capabilities without bulky hardware or complex setups.
- • **Blazing Fast AI Inference:** Dual Edge TPUs deliver up to 8 trillion operations per second with ultra-low 2W power consumption per TPU, powering real-time ML at nearly 400 FPS.
- • **Proven Stability & Efficiency:** Engineered for continuous, cool, and reliable operation—trusted by professionals for demanding AI workloads like video object detection.
- • **Ready for Cutting-Edge Models:** Native compatibility with TensorFlow Lite and AutoML Vision Edge lets you deploy state-of-the-art custom image classification models instantly.
- • **Seamless Cross-Platform Integration:** Plug-and-play support for Debian-based Linux and Windows 10 systems ensures effortless deployment in your existing infrastructure.

## Overview

The Coral M.2 Accelerator with Dual Edge TPU is a compact AI accelerator card featuring two Edge TPU coprocessors capable of delivering up to 8 TOPS combined performance at just 4 watts total. It supports Debian-based Linux and Windows 10, runs TensorFlow Lite and AutoML Vision Edge models, and is optimized for real-time, power-efficient machine learning tasks such as video object detection and custom image classification.

## Description

Product description The Coral M.2 Accelerator with Dual Edge TPU is an M.2 module (E-key) that includes two Edge TPU ML accelerators, each with their own PCIe Gen2 x1 interface. The Edge TPU is a small ASIC designed by Google that accelerates TensorFlow Lite models in a power efficient manner: each one is capable of performing 4 trillion operations per second (4 TOPS), using 2 watts of power—that's 2 TOPS per watt. For example, one Edge TPU can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 frames per second. This on-device ML processing reduces latency, increases data privacy, and removes the need for a constant internet connection. With the two Edge TPUs in this module, you can double the inferences per second (8 TOPS) in several ways, such as by running two models in parallel or pipelining one model across both Edge TPUs. Requirements A computer with one of the following operating systems Linux: 64-bit version of Debian 10 or Ubuntu 16.04 (or newer), and an x86-64 or ARMv8 system architecture Windows: 64-bit version of Windows 10, and x86-64 system architecture All systems require support for MSI-X as defined in the PCI 3.0 specification At least one available Mini PCIe or M.2 module slot Python 3.6-3.9 Edge TPU ML accelerator 2x Google Edge TPU ML accelerator ○ 8 TOPS total peak performance (int8) ○ 2 TOPS per watt Integrated power management 2x PCIe Gen2 x1 interface (one per Edge TPU) M.2-2230-D3-E module Size: 22.0 x 30.0 x 2.8 mm Operating temp: -40 to +85 °C

Review: Works great for YOLO - So far so good running YOLO on Frigate NVR. Detections are quick installation was easy using the correct adapter.
Review: Reseach before buying, less tears later... - Make sure you have compatible hardware. I bought this plus and adapter to use in my older SSSE3 capable motherboard, but the aging Google drivers, the compiled versions, only support SSE4.1 and up. Ended up compiling special drivers for Frigate and got it working. Dropped the CPU utilization to 30% for AI detection. BTW, this setup only supports one half of the TPU, since this is a dual core, but thats no problem for me and I knew that when buying. Learned a lot about "slots" during this buying process. I used this adapter "HLT M.2 (NGFF) to mPCIe (PCIe+USB) Adapter" to make it work in my Wifi card slot.

## Features

- Performs high-speed ML inferencing: Each Edge TPU coprocessor is capable of performing 4 trillion operations per second (4 TOPS), using 2 watts of power. 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. With the two Edge TPUs in this module, you can double the inferences per second (8 TOPS) in several ways, such as by running two models in parallel or pipelining one model across both Edge TPUs.
- Works with Debian Linux and Windows: Integrates with Debian-based Linux or Windows 10 systems with a compatible card module slot.
- 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. Description

## Technical Specifications

| Specification | Value |
|---------------|-------|
| ASIN | B0CY231Q61 |
| Best Sellers Rank | #1,550 in Single Board Computers (Computers & Accessories) |
| Brand | seeed studio |
| Built-In Media | / |
| Compatible Devices | Devices with a compatible card module slot and support for Debian Linux or Windows 10 |
| Connectivity Technology | PCIe |
| Customer Reviews | 4.1 out of 5 stars 78 Reviews |
| Included Components | / |
| Manufacturer | seeed studio |
| Mfr Part Number | 102110449-FA |
| Model Name | Coral M2 Accelerator with Dual Edge TPU |
| Model Number | Coral M.2 |
| Operating System | Debian-based |
| Processor Count | 2 |
| RAM Memory Technology | LPDDR4 |
| Smart Home Compatibility | Not Smart Home Compatible |
| Total Usb Ports | 1 |
| Unit Count | 1.0 Count |
| Warranty Description | 2 year |
| Wireless Communication Standard | Bluetooth |
| Wireless Compability | Bluetooth |

## Product Details

- **Brand:** seeed studio
- **Connectivity Technology:** PCIe
- **Included Components:** /
- **Model Name:** Coral M2 Accelerator with Dual Edge TPU
- **Operating System:** Debian-based

## Images

![Coral M.2 Accelerator with Dual Edge TPU … - Image 1](https://m.media-amazon.com/images/I/61GAqi4CkaL.jpg)
![Coral M.2 Accelerator with Dual Edge TPU … - Image 2](https://m.media-amazon.com/images/I/51NqTWAEWAL.jpg)
![Coral M.2 Accelerator with Dual Edge TPU … - Image 3](https://m.media-amazon.com/images/I/61M9kToShBL.jpg)
![Coral M.2 Accelerator with Dual Edge TPU … - Image 4](https://m.media-amazon.com/images/I/61TkyKRludL.jpg)
![Coral M.2 Accelerator with Dual Edge TPU … - Image 5](https://m.media-amazon.com/images/I/61i42Ub8asL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Works great for YOLO
*by J***E on April 19, 2026*

So far so good running YOLO on Frigate NVR. Detections are quick installation was easy using the correct adapter.

### ⭐⭐⭐⭐⭐ Reseach before buying, less tears later...
*by B***. on March 22, 2026*

Make sure you have compatible hardware. I bought this plus and adapter to use in my older SSSE3 capable motherboard, but the aging Google drivers, the compiled versions, only support SSE4.1 and up. Ended up compiling special drivers for Frigate and got it working. Dropped the CPU utilization to 30% for AI detection. BTW, this setup only supports one half of the TPU, since this is a dual core, but thats no problem for me and I knew that when buying. Learned a lot about "slots" during this buying process. I used this adapter "HLT M.2 (NGFF) to mPCIe (PCIe+USB) Adapter" to make it work in my Wifi card slot.

### ⭐ NOT a typical M.2 in 2026
*by T***Y on February 2, 2026*

Pay attention that it's an E-key and NOT M-Key; thus, you need to buy an adapter. I assmed that every M.2 should work with my QNAP NAS but I was wrong....big time! M.2 is a general concept and you need to know in adavnce what Key is suitable for your system. Ordered the adapter and still waiting to test this product. Please do ur homework first and see if this the right choice for you. Better off to buy the M.2 M-Key and pay a bit more than this useless E-Key that NO one is using in 2026!

## Frequently Bought Together

- Coral M.2 Accelerator with Dual Edge TPU …
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*Product available on Desertcart United Kingdom*
*Store origin: GB*
*Last updated: 2026-05-25*