Hailo-8 M.2 AI Accelerator Module Based On the 26TOPS Hailo-8 AI Processor Suitable For Raspberry Pi 5
Hailo-8 M.2 AI Accelerator Module, based on the 26TOPS Hailo-8 AI processor, Supports Linux/Windows Systems, Optional for PCIe To M.2 Adapter Board, Suitable For Raspberry Pi 5Hailo-8 AI KitEquipped With 26TOPS Hailo-8 M.2 AI Accelerator ModuleThis AI kit is launched by Waveshare to provide a more cost-effective and high-performance AI solution for the Raspberry Pi 5, optional for PCIe To M.2 adapter, suitable for applications such as process control, safety, home automation and robotics, etc.Fe
- Complete educational DIY robotics platform package
- Multiple degrees of freedom for realistic humanoid or quadruped movement
- Supports visual Scratch coding for beginners and Python for advanced users
- Equipped with high-performance metal gear servos and smart controllers
- Sturdy structural frame designed to withstand impact and stress
- Comprehensive step-by-step tutorials and rich sample code library
- Easily expandable with external sensors, cameras, and grippers
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(855) I-BUY-ROBO (855) 428-9762based on the 26TOPS Hailo-8 AI processor, Supports Linux/Windows
Systems, Optional for PCIe To M.2 Adapter Board, Suitable For Raspberry
Pi 5
Equipped With 26TOPS Hailo-8 M.2 AI Accelerator Module
This AI kit is launched by Waveshare to
provide a more cost-effective and high-performance AI solution for the
Raspberry Pi 5, optional for PCIe To M.2 adapter, suitable for
applications such as process control, safety, home automation and
robotics, etc.
- Hailo-8 AI M.2 module
Powered by 26 Tera-Operations Per Second (TOPS) Hailo-8 AI Processor
2.5W typical power consumption
Scalable,enabling simultaneous processingof multi-streams & multi-models
Enabling real-time, low latency and high-efficiency AI inferencing on the edge devices
Supports TensorFlow, TensorFlow Lite, ONNX, Keras, Pytorch frameworks
Supports Linux and Windows
Supports the temperature range of -40°C to 85°C
- PCIe To M.2 adapter
Onboard power monitoring chip and EEPROM, supports real-time monitoring of device power status for more stable operation
Raspberry Pi HAT+ compliant
Reserved airflow vent, supports installing cooling fan for better heat dissipation of the AI module to improve performance
Immersion gold process design, anti-oxidation and more durable
AI performance | 26 TOPS |
Form Factor | M.2 Key M |
Power supply | 3.3V ± 5% |
Power consumption | 2.5W (Typ.) |
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 | 22×80mm with breakable extensions to22×42mmand 22×60mm |
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.
NN Model | Input Resolution | mAP | Hailo-8L FPS |
yolov4_tiny | yolov4_tiny | 18.98 | 610 |
yolov6n | yolov6n | 34.3 | 345 |
yolov7 | yolov7 | 49.8 | 45 |
yolox_s_wide | yolox_s_wide | 42.4 | 75 |
yolov3 | yolov3 | 38 | 26 |
yolov8n | yolov8n | 37.23 | 270 |
yolov8s | yolov8s | 44.75 | 128 |
yolov8m | yolov8m | 50.08 | 55 |
Type | NN Model | Input Resolution | FPS | Power(W) | FPS/W |
Classification | ResNet-50 v1 | 224x224 | 1332 | 3.45 | 386 |
MobileNet_v2_1.0 | 224x224 | 2444 | 2.152 | 1135 | |
EfficientNet_M | 240x240 | 889 | 3.5 | 254 | |
Object Detection | SSD_MobileNet_v1 | 300x300 | 1055 | 2.2 | 479 |
YOLOv5m | 640x640 | 218 | 4.6 | 47.3 | |
Segmentation | stdc1 | 1024x1920 | 54 | 2.9 | 18.6 |
Multi stream object detection (8 streams) | YOLOv3 | 608x608 | 69 | 4.9 | 14 |
Based on 16PIN PCIe Interface of Raspberry Pi 5
Standard Raspberry Pi 40PIN Header, Comes
with 2*20 Pin header for Stacking with Other HATs. Compact Size, More
Space-Saving, supports installing cooling fan
can be used together with the Pi5 Active Cooler Bto achieve better heat dissipation effect For the Pi5 And AI
Accelerator Module, keeping it cool even under heavy processing and
maximizing the Module Performance
Real-time monitoring of device power status for More Stable operation
* for reference only, the cooling fan is NOT included.
Packing List
Hailo-8
Hailo-8 AI M.2 Module ×1
Use Cases
STEM classrooms, programming labs, motion control algorithms, autonomous navigation testing, and personal learning projects.
Compatibility Notes
Fully programmable via Scratch visual block editor, Python, or C++ APIs. Requires rechargeable batteries and a desktop computer for code uploads.
Frequently Asked Questions
No, the kit features plug-and-play electronic connections and mechanical screw fasteners, making assembly clean and safe.
This kit is ideal for students aged 12 and up due to its assembly complexity, and younger builders with adult guidance.
Yes, all sample scripts, library wrappers, and firmware configurations are open-source and available for custom modifications.
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