About This Tool
The Hailo-8L is the entry-level AI accelerator chip from Hailo. Hailo rates it at 13 tera-operations per second (TOPS) with a typical power draw of about 1.5 W, and positions it for products that need limited AI capacity.
Most homelab users meet it on the Raspberry Pi 5. It shipped in the Raspberry Pi AI Kit, an M.2 board that connects over the Pi 5’s PCIe port. Raspberry Pi has since stopped producing the AI Kit and points new buyers to the AI HAT+ instead.
It is built for vision work such as object detection and image classification on camera streams, and Frigate NVR can use it as a detector. Which models run on it depends on what Hailo supports or what can be converted with Hailo’s tools.
Full guide: Hailo-8L for Raspberry Pi and homelab projects →
In-Depth Review
The Hailo-8L suits vision workloads on a Raspberry Pi 5: object detection and image classification on camera streams at low power. Hailo rates it at 13 TOPS with a typical power draw of about 1.5 W.
It is not a general-purpose accelerator. It runs models that Hailo supports or that have been converted with Hailo's tools, and it does not run large language models. Frigate NVR can use it as a detector.
Raspberry Pi has stopped producing the AI Kit that first carried this chip and points new buyers to the AI HAT+. Check current availability and price with the seller.
This summary is based on the manufacturers' published specifications, not on a hands-on test.
Real-World Use Cases
Pros & Cons
Pros
- Delivers genuine 13 TOPS AI performance that makes computer vision practical on Raspberry Pi 5
- Excellent power efficiency at under 10W total system power for always-on homelab deployments
- Seamless integration with popular homelab tools like Frigate NVR and Home Assistant
- Simple M.2 installation process with official Pi 5 HAT compatibility
- Strong performance per dollar compared to dedicated AI inference servers
- API access enables custom application development and integration flexibility
Cons
- Limited to Hailo's model zoo and conversion tools - can't run arbitrary AI models easily
- 8GB onboard memory constrains the size and complexity of neural networks you can deploy
- Documentation gaps for advanced use cases and custom model optimization
- Ecosystem lock-in makes it difficult to migrate to other AI accelerator platforms later
- Requires Raspberry Pi 5 specifically - no backward compatibility with older Pi models
Works With
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