Hailo-8 vs Hailo-8L: Key Differences Compared

Power at the Edge: Choosing Between the Hailo-8 and Hailo-8L

When it comes to supercharging edge devices—ranging from smart home security setups and robotics to industrial automation—dedicated AI accelerators have completely changed the game. Instead of relying on power-hungry GPUs or straining a device’s main CPU, specialized neural processing units (NPUs) get the heavy lifting done efficiently.

Among the top contenders in this space are the Hailo-8 and its sibling, the Hailo-8L. Both chips deliver incredible data-center-class performance to compact hardware (like the Raspberry Pi 5 via AI HATs), but they target slightly different needs.

The Core Difference: Raw Power (TOPS)

At a glance, the main distinction between the two processors comes down to processing capacity:

• Hailo-8: The heavy hitter of the pair, packing a punch with up to 26 TOPS (Tera-Operations Per Second) of INT8 performance.
• Hailo-8L: The “entry-level” or light vision option, delivering up to 13 TOPS of INT8 performance. Essentially, the Hailo-8L features half of the core compute resources of the standard Hailo-8 while maintaining the same architectural speed.

Head-to-Head Comparison

| Feature | Hailo-8 | Hailo-8L |
| :— | :— | :— |
| Peak Performance | 26 TOPS (INT8) | 13 TOPS (INT8) |
| Target Use Case | Demanding computer vision, multi-stream video, concurrent models | Cost-sensitive object detection, moderate edge vision |
| Form Factors | M.2 Key M, B+M, A+E | M.2 Key B+M, A+E |
| Software Support | TensorFlow, PyTorch, ONNX, Keras | TensorFlow, PyTorch, ONNX, Keras |
| Power Efficiency | Exceptional (Ultra-low power TDP) | Exceptional (Optimized for lower power draws) |

Which One Should You Choose?

Deciding which accelerator fits your project depends entirely on what you want your device to accomplish:

Go with the Hailo-8L if:

• You are working on a budget: It is the more cost-effective choice for lighter tasks.
• Your project is straightforward: If you are running a single video stream for standard object detection (like basic security camera tracking or simple automation), 13 TOPS provides more than enough headroom.
• Power and thermal limits are tight: Its scaled-down resource footprint makes it a breeze to cool in tight, compact enclosures.

Go with the Hailo-8 if:

• You are running heavy workloads: If your edge device needs to process multiple high-resolution video streams simultaneously or run several complex neural networks at once, you will appreciate the extra 26 TOPS muscle.
• You want future-proofing headroom: Even if your current model runs fine on 13 TOPS, choosing the Hailo-8 gives you room to scale up to heavier, more accurate models down the road without changing your hardware.

Final Thoughts

Both processors share the same robust software ecosystem, supporting standard frameworks like TensorFlow and PyTorch alongside Hailo’s comprehensive Dataflow Compiler. This means code written for one can easily transition to the other.

If you are building a lightweight, cost-conscious smart camera or single-task monitor, the Hailo-8L hits the sweet spot. If you are engineering a multi-camera powerhouse or an industrial-grade vision system that demands maximum throughput, the Hailo-8 is worth every extra bit of performance.