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waveshare

waveshare Hailo-8 M.2 AI Accelerator Module, Compatible with Raspberry Pi 5, Supports Linux/Windows Systems, Based On The 26TOPS Hailo-8 AI Processor, Module Only

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This item's return window has been extended for the holiday season: Returnable until Jan 31, 2026

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Availability: Only 2 left in stock, order soon!
Fulfilled by Amazon
Arrives Saturday, Jan 10
Order within 15 hours and 45 minutes
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Features

  • Powered by 26 Tera-Operations Per Second (TOPS) Hailo-8 AI Processor. 2.5W typical power consumption
  • Scalable, enabling simultaneous processing of 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 -40C to 85C
  • Rich WiKi Resources We provide official Wiki resources, please contact us for more information.

Graphics Coprocessor: Integrated Graphics


Brand: waveshare


Video Output Interface: HDMI, DisplayPort


Graphics Processor Manufacturer: Intel or AMD


Graphics RAM Type: GDDR6


Package Dimensions: 3.1 x 2.7 x 1.1 inches


Item Weight: 0.32 ounces


Manufacturer: Waveshare


Item model number: Hailo-8


Date First Available: July 8, 2024


Frequently asked questions

If you place your order now, the estimated arrival date for this product is: Saturday, Jan 10

Yes, absolutely! You may return this product for a full refund within 30 days of receiving it.

To initiate a return, please visit our Returns Center.

View our full returns policy here.

  • Klarna Financing
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  • Financing through Apple Pay
Leasing options through Acima may also be available during checkout.

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Top Amazon Reviews

    • Great accelerator for video (Frigate)
This thing is fast and powerful, perhaps too much for my use case, but at least I have room to grow. I'm feeding this chip two 1280x720 video streams at 16 FPS, through the premium Frigate+ "yolov9s" model (640x640), tracking 13 kinds of objects each! It reports an 18ms average inference time, and it rarely passes 16% CPU with large objects moving in both cameras simultaneously. Detections are butter smooth and very accurate. ... show more
Reviewed in the United States on October 26, 2025 by KZ
    • Working great with Frigate
So far I am happy with this and Frigate. I was running BlueIris on a PC with a GTX1050 where inference times were around 120-175ms on my cameras. I wanted to switch to Frigate and use the GPU for something else. It's reporting 10-20ms inference times and is noticably faster on notifications. Thats even using the full 2k stream on 2 of my cameras and it identifies people much further away. I had read in forums that people were able to use this with a usb-c adapter but I wasn't able to get that working. I had to swap drives since the mini PC only had 1 nvme and 1 SATA m.2 slot, and this will only work in the nvme slot. Overall I'm happy with it so far. ... show more
Reviewed in the United States on June 29, 2025 by Jeepin
    • Came with nothing
Haven't even tested the module yet, it came without anything. Absolutely nothing. No instructions, and more importantly, NO HEATSINKS or any type of cooling. Not sure if I should chance it or not until I find some cooling product that fits it. UPDATE: Useless to run Ollama on a Raspberry Pi 5. I have no use for it if an Ai Accelerator Module can't be used for an Ai process that consumers actually care about. ... show more
Reviewed in the United States on December 3, 2024 by Souperman

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