Coral M.2 Accelerator with Dual Edge TPU …

I use this with the free/open source Frigate NVR software that is connected to my Home Assistant. I have an HP EliteDesk 705 that I took out the wifi/bluetooth card because I use a hardwired LAN connection and put this Coral in instead. Sadly it only detects one of the TPUs, but that's not the Coral's fault, it's a limitation on my computer.

This Coral M.2 Accelerator works flawlessly. I added it to my server specifically for AI object detection with Frigate, and the performance jump is incredible. The dual Edge TPU handles real-time detection smoothly, runs cool, and stays completely stable. Setup was quick, and it integrated with my system without any issues. If you’re using Frigate or need solid hardware acceleration for machine learning tasks, this is absolutely worth it.

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!

Used this to integrate first into a blue iris camera system for object detection. I later switched to frigate and again, it's worked without issue. Excellent quality product and fits my needs perfectly. Low power ai object recognition.

As others have pointed out, the "Coral" device itself is great; however you need to be extra careful which M.2 version you get. I had to return these for the M.2 A+E key version as I removed a M.2 WiFi card and wanted to replace it with a M.2 Coral. THIS version of the device will likely NOT work with your motherboard, look for the A+E key version instead. That unit works good on Linux (had to manually build a DKMS module for it to work on Ubuntu 24.04) and Frigate integration is pretty straight forward. Frigate shows an inference speed of 7.5ms and the device runs at 51°C.

This was a huge pain in the A$$ to set up. I purchased it as an upgrade from my coral USB accelorator. Only to find it out was a nightmare to get up and running in on my raspberry pi. Mainly because Google abandoned the project 3 years ago. Meaning they havnt updated anything. One of those things is the version of python. The libraries you need run on an older version of python and Raspberry Pis OS comes with the latest version. I had to find an older version of debian LINUX that still used it and run a docker container just to set everything up. WAS NOT fun and I essentially was so disappointed, havnt used it much since. You can still use it to increase your inference rate for training your Ai model, but keep running into so many issues it's really not worth thr hassle I woukd not suggest buying one unless support and development has inprocd

Received an defective item. The customer service is great!

Works great with Frigate.

not working at all

Works wonders!

TPU détecté, mais pour ce qui est du contenu du colis, il n'y aura que le tpu en lui-même. Pas de dissipateur thermique, manuel d'utilisation comme promis dans la description! J'ai posé la question au vendeur, mais pas de retour! Cordialement.

Viene sin caja, metido en una bolsa de plástico de burbujas, y esta a su vez en otra. Un producto muy pequeño, delicado y sin caja del fabricante. Parece de segunda mano o de baja calidad. Aún no la he instalado. Espero funcione. Muy mala presentación para ser tan cara.

Shoved this in my qnap to speed up the QuMagie AI. Works great shows up as 2 TPU's but had to buy a special multiplexing adapter to an m.2 slot and then also get a m.2 to pci slot card. But that's as much to do with the qnap as the card itself.