Hailo-8 vs. Hailo-8L: Choosing the Right Edge AI Accelerator

Edge AI has revolutionized how smart devices interact with the world, shifting processing from distant cloud servers to local, power-efficient hardware. Among the leaders in this space is Hailo, known for its dataflow-oriented AI processors that deliver massive performance without requiring active, heavy-duty server cooling.

If you are designing an embedded system, upgrading a single-board computer like the Raspberry Pi, or setting up a local machine-vision system (such as Frigate NVR), you have likely encountered Hailo’s two flagship chips: the Hailo-8 and its streamlined sibling, the Hailo-8L.

While they look similar on paper, understanding their distinct performance profiles, hardware interfaces, and use cases is essential to choosing the right option for your project.

1. Core Specifications at a Glance

At their structural core, the Hailo-8 and Hailo-8L share the same underlying architecture and software toolchain. The primary differentiator is raw compute scale:

| Feature | Hailo-8 | Hailo-8L |
| :— | :— | :— |
| Peak Performance (INT8) | 26 TOPS | 13 TOPS |
| Compute Resources | Full architecture layout | Exactly half the compute elements of the Hailo-8 |
| Form Factors | M.2 (Key M, Key B+M, Key A+E) | M.2 (Key B+M, Key A+E) |
| PCIe Interface | Up to PCIe Gen3 x4 (on Key M variants) | PCIe Gen3 x2 |
| Typical Power Consumption | ~2.5W to ~8.25W (workload dependent) | ~2.5W to ~6.6W (workload dependent) |
| Target Application | Heavy vision, multi-stream, complex/parallel models | Entry-to-mid level vision, cost-sensitive edge devices |

2. Deconstructing the Differences

Performance & Compute (26 TOPS vs. 13 TOPS)

The Hailo-8 delivers up to 26 tera-operations per second (TOPS) using INT8 precision. The Hailo-8L is engineered as a lower-cost vision option and features precisely half the compute resources, rated at 13 TOPS.