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I don't know, they look like the ones in the picture, they are very uncomfortable and I ordered them in brown, not black.
The product is fake and very bad, the processor is i3 and the RAM is DDR3.
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Hailo Ai Acceleration Module
Regular price
$816.86
Sale price
$692.25
In stock. Ready to ship.
This discount is based on purchasing the main product
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Estimated between Oct 13, 2026 and Oct 15, 2026 Ships within 1-3 business day after payment clears. | SHOP Track Order | Ourlum Orders | Track Orders
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Hailo Ai Acceleration Module
Regular price
$816.86
Sale price
$692.25
Hailo Ai Acceleration Module
Deploy edge AI faster with the Hailo 8 M.2 acceleration module. This new EASY EAI board delivers 26 TOPS INT8 performance for rapid neural processing. The chip maintains stable throughput across harsh -40°C to 80°C ranges. You gain dependable compute power for IoT prototypes and commercial sensor arrays.
Key Features
The compact M.2 footprint slides securely into standard expansion connectors. Factory-tested calibration guarantees consistent inference latency. Shipped in protective anti-static packaging to preserve pin integrity.
Product Description
You receive a purpose-built accelerator engineered for modern neural networks. The module executes quantized models without draining your host processor bandwidth. Official documentation and verified code examples streamline your initial integration phase.
Product Overview
This is a high-density edge processor constructed for developers who prioritize speed. System architects embed it into carrier designs for local model execution. The architecture supports rapid prototyping phases and scalable manufacturing lines.
Key Benefits
Offload heavy tensor calculations so your central controller manages background tasks. Run computer vision pipelines locally with reduced network overhead. Lower recurring server costs while preserving strict privacy boundaries.
Features
- High Throughput: Delivers 26 TOPS under INT8 precision for demanding workloads.
- Extended Thermal Design: Operates reliably across -40°C to 80°C environments.
- Plug-and-Play Mount: Follows standard M.2 spacing for quick board installation.
Specifications
Peak integer throughput reaches 26 TOPS. Functional window spans -40°C to 80°C without thermal throttling. Constructed without high-concern chemical compounds. Sourced directly from Guangzhou EASY EAI Technology Co., Ltd.
What’s Included
Your package arrives containing one factory-fresh Hailo 8 M.2 acceleration module. Compatible mounting screws and thermal pads ship separately depending on your baseboard selection. Match the keying notch to your motherboard slot before closing the chassis.
How to Use
Align the connector index with the designated M.2 slot on your development board. Secure the fastener firmly to prevent vibration loosening. Upload quantized model files using the supported compiler suite provided in our technical portal.
Customer Benefits
Execute inference tasks completely offline without waiting for remote servers. Scale batch processing efficiently since the hardware handles parallel data streams. Maintain consistent frame rates that keep automated monitoring systems responsive.
Ideal Uses
Analyze live camera feeds for facial recognition inside secure warehouse entryways. Process voice commands locally inside noise-prone retail kiosks. Drive obstacle avoidance logic for small autonomous mobile robots.
Who It’s For
Embedded software engineers designing next-generation smart appliances. Automation specialists deploying predictive maintenance sensors. Academic researchers testing large dataset reductions on standalone rigs.
5 Frequently Asked Questions
Does this module support traditional graphics rendering?
No. It utilizes a specialized neural processing architecture optimized strictly for matrix multiplication and tensor operations.
Can I execute transformer-based language models here?
Yes. The 26 TOPS INT8 engine efficiently quantizes attention layers for practical edge deployment.
Hailo Ai Acceleration Module: review the specifications and available configurations.
Product identification: Hailo 8 M.2 Ai Acceleration Module
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C
Simply FANTASTIC, arrived very well packaged in a custom Hailo box, worked perfectly with my N100 running Frigate for 6 cameras, with a temperature around 75ºC, running MobileNet v1.
S
Real deal! Identifies and performs as hailo-8 should. Frigate runs smoothly using yolov11s detector.
# Docker exec frigate hailortcli fw-control identify
Executing on device: 0000:04:00.0
Identifying board
Control protocol version: 2
Firmware version: 4.21.0 (release,app,extended context switch buffer)
Logger version: 0
Board name: hailo-8
Device architecture: hailo8
L
I checked, it works and is detected by the lspci command.
S
The module is genuine hailo-8 with 26 tops. Module when inserted into nvme m.2 slot (not just sata m.2) is recognized both in windows (hwinfo64) and linux (tried ubuntu). I have used it to build a designated nvr - inserted the module to a mini pc, installed ubuntu lts and drivers, frigate in docker and paired it to my home assistant. Works perfectlybwith frigate and yolov9s model. Much less false detections than with coral and now i can also run detection on higher resolution streams.
Shipping was fast and packaging good - module in sealed bag, well packed in bubble wrap and shipped in a plastic box. Price could be better, especially when compared to raspberry ai hat which is basically the same chip just not in m.2 forman. However, i wanted the m.2 version for the mini pc and compated to other such version this price is reasonable. Overall, i am satisfied with the product and the seller.
M
It arrived on time!
C
Everything is as described, managed to run it on TrueNas Scale 25.10.2.1 - Goldeye. There is no driver 21 for the newer version of TrueNas and it needs to be activated in Frigate.
D
Thankyou seller, the module has arrived in good order, and well packaged.
J
Sold broken in an intact box. It's not that it doesn't work, it's that I have to wait another 3 weeks to use it because I need to wait for the NMVe extension adapter to hold it in place. The seller is trying to get away with it by sending back photos that have nothing to do with the problem.
J
Great price, considering how difficult these are to find.
Works perfectly in my frigate setup.
Arrived in the uk in a week.
N
Installed it in RP5 via the M2 board. Everything works perfectly with Frigate, the objects are detected. I installed an additional heatsink on the board and am cooling everything with a fan, but there is still a slight amount of heat. RP5 16GB (8GB would be sufficient) + Hailo 8 can handle 10 FullHD + 2 4K cameras, CPU load on RP is 30-50% depending on traffic intensity, detector time is 30-40ms. I am very satisfied with the system. Intel+Nvidia would handle around 300W, but here it's no more than 15W. I'll be honest, I had a bit of a struggle with selecting the drivers and the Linux kernel, but only for those who aren't afraid of challenges and understand why it's necessary!
E
Great, I managed to compile the driver for DSM7.2 (xpenology), and it works perfectly with Fridge.
K
The order has been received. Thank you very much.
C
All good very good 👍
C
It works. But the textolite was broken off, so I had to buy an adapter.
