seeed studioCoral M.2 Accelerator A+E Key
Details
- Brandseeed studio
- Model NameCoral M.2 A+E
- Connectivity TechnologyM.2 A+E key
- Included Components/
- Operating SystemDebian-based
Description
đ Turbocharge your edge AI with power and precision!
- TENSOR FLOW LITE READY - Run pre-built models instantly without complex setup or retraining.
- CUSTOM AI MODELS MADE EASY - Supports AutoML Vision Edge for quick, high-accuracy custom image classification.
- BLAZING FAST ML INFERENCING - Delivers 4 trillion operations per second for real-time AI at the edge.
- POWER EFFICIENT PERFORMANCE - Achieves 2 TOPS per watt, maximizing output while minimizing energy use.
- PLUG PLAY DEBIAN COMPATIBILITY - Works effortlessly with any Debian-based Linux system for instant deployment.
The seeed studio Coral M.2 Accelerator A+E Key is a compact, energy-efficient AI accelerator card featuring an Edge TPU coprocessor capable of 4 TOPS. Designed for Debian-based Linux systems, it supports TensorFlow Lite and AutoML Vision Edge, enabling rapid deployment of high-speed, custom machine learning models at the edge.
Specifications
| RAM | LPDDR4 |
| Brand | seeed studio |
| Series | Coral M.2 Accelerator A+E Key |
| Operating System | Debian-based Linux |
| Item Weight | 0.317 ounces |
| Package Dimensions | 4 x 2.5 x 0.2 inches |
| Processor Brand | ARM |
| Number of Processors | 1 |
| Manufacturer | seeed studio |
| ASIN | B0DFMC1GQF |
| Date First Available | August 29, 2024 |
Reviews
C**S
AI detections in Blue Iris.
Works good for adding Cotal for Blue Iris. It definitely saves on CPU power.
J**F
Works
Works perfectly. Excellent value. Use it to acelerate AI detecton in video. Delivered on time.
B**E
Still useful for Frigate
If you're shopping for this, you know what it's for.Confirmed fit in NUC8i7HNK and passthrough from Proxmox->LXC->Docker
T**2
Works great, at least with Frigate
Have this in a NUC size server and it works great with frigate running in a container. Works great to identify humans and most parts of humans (head, hand, etc.). Tested it in my office and had the camera looking out the door, 97% accuracy recognizing one of my dogs when they'd look in the door or walk past. Frigate would occasionally think they were a cat if they walked past the door quick enough that the low frame rate missed their head and only got a body and tail.Granted Frigate can do the image recognition without an Edge, but the Edge significantly increases the speed and reduces the processing power required so I can handle many more cameras.
T**C
Reduces CPU load substantially
Using this on a Ryzen laptop with Frigate on Ubuntu 24.04. Instead of a detection event pegging a core for 25-30 seconds, it only uses up about 10% of a core for 5-6 seconds. Can't wait to see how it scales to more cameras. Just quadruple-check your keying before buying--the A+E key is narrower than older laptops that use PCI-e. (The edge connector is 2 cm wide on the A+E key vs. 2.5 cm for the old PCI-e.)
W**E
Does what's it's supposed to do
Does what's it supposed to do. I use it to process object detection on a blue iris NVR. I'm not sure if it's my system or the coral TPU itself, but it sometimes seems to crash for a quick second and start using the CPU. However it would automatically switch back to using the coral TPU on its own. Overall I'm happy with it.
T**E
Working great in my Beelink EQ12
Works great in my Beelink EQ12. (DOES NOT WORK WITH S12 pro)You should do your research on your specific device to make sure the WiFi slot will take this thing. YMMV.Frigate is seeing and utilized it with no friction at all
D**G
Works great.
I installed it in place of the WIFI/Bluetooth module in a GMKTec Mini PC and install Frigate for my Home assistant cameras. It is working well detecting cars and animals on two cameras pointed at my driveway and garden.
Common Questions
Trustpilot
2 months ago
2 weeks ago
