--- product_id: 627674247 title: "Coral M.2 Accelerator with Dual Edge TPU …" brand: "seeed studio" price: "$2.69" currency: USD in_stock: false reviews_count: 13 url: https://www.desertcart.ec/products/627674247-coral-m-2-accelerator-with-dual-edge-tpu store_origin: EC region: Ecuador --- # 8 TOPS peak performance 2 TOPS per watt power efficiency Dual PCIe Gen2 x1 interfaces Coral M.2 Accelerator with Dual Edge TPU … **Brand:** seeed studio **Price:** $2.69 **Availability:** ❌ Out of Stock ## Summary > πŸš€ Double the TPU, double the AI power β€” accelerate your edge computing game! ## Quick Answers - **What is this?** Coral M.2 Accelerator with Dual Edge TPU … by seeed studio - **How much does it cost?** $2.69 with free shipping - **Is it available?** Currently out of stock - **Where can I buy it?** [www.desertcart.ec](https://www.desertcart.ec/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 - β€’ **TensorFlow Lite Ready:** Run cutting-edge ML models instantly without rebuilding from scratch. - β€’ **Power-Savvy Performance:** Maximize efficiency with 2 TOPS per watt, keeping your system cool and green. - β€’ **Seamless OS Integration:** Plug-and-play support for Debian Linux and Windows 10 ensures smooth deployment. - β€’ **Blazing Fast ML Inferencing:** Harness 8 trillion operations per second with dual Edge TPUs for lightning-quick AI insights. - β€’ **Custom AI at Your Fingertips:** Leverage AutoML Vision Edge to create and deploy high-accuracy custom image classifiers effortlessly. ## Overview The Coral M.2 Accelerator with Dual Edge TPU is a compact M.2 module featuring two Google-designed Edge TPU coprocessors, delivering a combined 8 TOPS of ML inferencing power at just 4 watts total. It supports Debian Linux and Windows 10, accelerates TensorFlow Lite models, and enables custom AI model deployment via AutoML Vision Edge. Ideal for professionals seeking ultra-fast, power-efficient on-device machine learning with minimal latency and enhanced data privacy. ## 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 powerβ€”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 β—‹ 8 TOPS total peak performance (int8) β—‹ 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 Β°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 … - Amcrest 5MP Turret POE Camera, UltraHD Outdoor IP Camera POE with Mic/Audio, 5-Megapixel Security Surveillance Cameras, 98ft NightVision, 132Β° FOV, MicroSD (256GB), (IP5M-T1179EW-AI-V3) --- ## Why Shop on Desertcart? - πŸ›’ **Trusted by 1.3+ Million Shoppers** β€” Serving international shoppers since 2016 - 🌍 **Shop Globally** β€” Access 737+ million products across 21 categories - πŸ’° **No Hidden Fees** β€” All customs, duties, and taxes included in the price - πŸ”„ **15-Day Free Returns** β€” Hassle-free returns (30 days for PRO members) - πŸ”’ **Secure Payments** β€” Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** β€” Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.ec/products/627674247-coral-m-2-accelerator-with-dual-edge-tpu](https://www.desertcart.ec/products/627674247-coral-m-2-accelerator-with-dual-edge-tpu) --- *Product available on Desertcart Ecuador* *Store origin: EC* *Last updated: 2026-06-18*