Hailo-8 M.2 AI Accelerator Module, based on the 26TOPS Hailo-8 AI processor, Supports Linux/Windows Systems
$179.99
Hailo-8 AI M.2 Module Parameters
| AI performance | 26 TOPS |
|---|---|
| Form Factor | M.2 Key M |
| Power supply | 3.3V ± 5% |
| Power consumption | 2.5W (Typ.) 8.65W (Max.) |
| Interface | PCIe Gen3, 4-lane |
| Certificate | CE, FCC Class A |
| Storage temperature | -40 ~ 85°C |
| Operating temperature | -40 ~ 85°C |
| Operating humidity | 5% ~ 90%RH (no frosting) |
| Dimensions | 22×42 (mm) |
Equipped with Hailo-8 AI Accelerator to Step Up Your Edge Product Performance
The Hailo-8 M.2 module is an AI accelerator module for AI applications, based on the 26 tera-operations per second (TOPS) Hailo-8 AI processor with high power efficiency. The M.2 AI accelerator features a full PCIe Gen-3.0 4-lane interface, delivering unprecedented AI performance for edge devices.
The M.2 module can be plugged into an existing edge device with M.2 socket to provide low-power deep neural network inferencing. Leveraging Hailo’s comprehensive Dataflow Compiler and its support for standard AI frameworks, customers can easily port their Neural Network models to the Hailo-8 and introduce high-performance AI products to the market quickly.
Hailo-8 performance parameters
| NN Model | mAP | Hailo-8L FPS (batch8) |
|---|---|---|
| yolov4_tiny | 18.98 | 610 |
| yolov6n | 34.3 | 345 |
| yolov7 | 49.8 | 45 |
| yolox_s_wide | 42.4 | 75 |
| yolov3 | 38 | 26 |
| yolov8n | 37.23 | 270 |
| yolov8s | 44.75 | 128 |
| yolov8m | 50.08 | 55 |
| Type | NN Model | Input Resolution | FPS | Power(W) | FPS/W |
|---|---|---|---|---|---|
| Classification | ResNet-50 v1 | 224×224 | 1332 | 3.45 | 386 |
| MobileNet_v2_1.0 | 224×224 | 2444 | 2.152 | 1135 | |
| EfficientNet_M | 240×240 | 889 | 3.5 | 254 | |
| Object Detection | SSD_MobileNet_v1 | 300×300 | 1055 | 2.2 | 479 |
| YOLOv5m | 640×640 | 218 | 4.6 | 47.3 | |
| Segmentation | stdc1 | 1024×1920 | 54 | 2.9 | 18.6 |
| Multi stream object detection (8 streams) | YOLOv3 | 608×608 | 69 | 4.9 | 14 |
Applied in the AI Field
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