Hailo-8 vs Hailo-8L Comparison: Specs & Performance

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

As edge computing continues to mature, bringing artificial intelligence directly to local hardware rather than relying on the cloud has become standard practice for robotics, smart cameras, and single-board computers like the Raspberry Pi. Among the leading contenders for low-power edge acceleration are Hailo’s compact processors.

Within their lineup, the Hailo-8 and the Hailo-8L stand out as two of the most popular choices for vision-based AI. While they share the same underlying architecture and software ecosystem, they target different performance brackets and budgets.

Quick Comparison At-a-Glance

| Feature | Hailo-8 | Hailo-8L |
| :— | :— | :— |
| Performance | 26 TOPS (INT8) | 13 TOPS (INT8) |
| Compute Resources | Full architecture array | Half the compute resources of Hailo-8 |
| Form Factors | M.2 Key M (PCIe Gen3 x4), B+M, A+E | M.2 Key B+M, A+E (PCIe Gen3 x2) |
| Typical Power Consumption | Up to ~8.25W max (workload dependent) | Up to ~6.6W max (workload dependent) |
| Ideal For | Multi-stream video, complex networks, parallel models | Cost-sensitive setups, single-stream NVRs, entry-level IoT |

Hailo-8: The Performance Heavyweight

The Hailo-8 is engineered for demanding computer vision tasks that require high throughput and minimal latency. Delivering up to 26 TOPS (Tera Operations Per Second) using INT8 precision, it punches well above its weight class while maintaining an impressively low power footprint.

• Key Strengths:
  • Parallel Model Execution: Capable of running multiple concurrent neural networks simultaneously without major performance degradation.
  • Multi-Stream Capability: Excellent for security systems or industrial setups processing multiple high-definition camera feeds at once.
  • High-End Connectivity: Frequently packaged in M.2 Key M formats utilizing four PCIe Gen3 lanes for maximum data bandwidth.
• Best Used For: Advanced robotics, dense object tracking, multi-camera smart city deployments, and complex industrial vision systems where accuracy and frame rate headroom are non-negotiable.

Hailo-8L: The Value and Efficiency Champion

The Hailo-8L is designed as a streamlined, budget-friendly entry point into edge AI. It features half the compute elements of its bigger sibling, delivering 13 TOPS of performance. Crucially, it retains the same core architecture and clock speed efficiency as the standard Hailo-8, making it a reliable and deterministic accelerator.

• Key Strengths:
  • Cost-Effectiveness: Significantly lowers the financial barrier for projects that require dedicated hardware acceleration.
  • Ecosystem Integration: Widely adopted in official maker hardware, such as the Raspberry Pi AI HAT+ ecosystem, for accessible local vision processing.
  • Power Efficiency: Draws slightly less power under maximum load, making it ideal for thermally constrained or battery-conscious enclosures.
• Best Used For: Single-camera Home NVR setups (such as Frigate installations), moderate object detection tasks, basic smart home automation, and lightweight edge appliances.

Software Integration and Compilation

One important technical detail to keep in mind when working with these accelerators is model compilation. Both chips utilize the Hailo Dataflow Compiler and run HEF (Hailo Executable Format) binary files.

However, because the Hailo-8L has distinct hardware resource constraints compared to the full Hailo-8, compiled binaries are not directly interchangeable. If you develop or optimize a custom model (like a specialized YOLO variant), you must compile the model specifically targeting the chosen architecture flag (hailo8 vs hailo8l). Fortunately, the toolchain makes this transition straightforward as long as the source model fits within the smaller layer and memory limits of the 13 TOPS variant.

Summary: Which One Should You Choose?

• Choose the Hailo-8 if: Your project involves multiple video streams, heavy models (like segmentation or complex pose estimation), or concurrent neural networks running side-by-side where frame rate drops are unacceptable.
• Choose the Hailo-8L if: You are building a cost-sensitive application, targeting a single camera feed (like a standard home security setup), or utilizing standard maker kits where 13 TOPS provides more than enough overhead for your workflow.