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

As edge computing and local artificial intelligence continue to transform everything from smart home automation to industrial robotics, efficient hardware is more critical than ever. Power-hungry GPUs are rarely practical outside of data centers, creating a massive demand for dedicated AI accelerators that deliver high performance on minimal power.

Among the standout solutions in the market are Hailo’s specialized processors. For builders deploying computer vision and neural networks at the edge—especially within popular ecosystems like the Raspberry Pi or custom NVR setups (such as Frigate)—two chips frequently come up: the Hailo-8 and its streamlined sibling, the Hailo-8L.

What separates these two power-efficient processors, and which one belongs in your next project? Let’s dive into a comprehensive head-to-head comparison.

1. Core Architecture and Performance: The Numbers Game

At a fundamental level, the Hailo-8L is designed as a lower-cost, lower-power companion to the full-fat Hailo-8. Architectural sharing runs deep between the two, but their raw computing capacity differs distinctly:

| Feature | Hailo-8 | Hailo-8L |
| :— | :— | :— |
| Peak Performance (INT8) | 26 TOPS (Tera Operations Per Second) | 13 TOPS |
| Compute Elements | Full complement | Exactly half of the Hailo-8 |
| Typical Power Consumption | ~2.5W – 8.25W (depending on workload/form factor) | ~1.5W – 6.6W (depending on workload/form factor) |
| 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 M-key variant) | Typically PCIe Gen3 x2 |

In essence, the Hailo-8L features roughly half the amount of compute elements found in the standard Hailo-8. Consequently, its advertised performance metric sits at 13 TOPS, exactly half of the Hailo-8’s 26 TOPS.