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The Hailo-8 M.2 AI Acceleration Module (HM218B1C2ZAE) delivers up to 26 TOPS of on-device AI inference performance in an M.2 2280 B+M Key form factor. Using a PCIe Gen 3 x2 interface with typical power consumption of approximately 2.5 W, this extended-temperature AI accelerator is designed for real-time computer vision, video analytics, machine vision, robotics and industrial edge AI applications..
The Hailo-8 M.2 AI Acceleration Module HM218B1C2ZAE is a high-performance edge AI accelerator starter kit designed to add dedicated neural-network inference capability to compatible embedded computers, industrial PCs, edge gateways and other systems with an M.2 interface.
Powered by the Hailo-8 AI processor, the module delivers up to 26 TOPS of AI inference performance while maintaining low typical power consumption of approximately 2.5 W. This combination allows demanding deep-learning workloads to run directly on edge devices, reducing reliance on cloud infrastructure and enabling faster local decision-making.
The HM218B1C2ZAE uses the standard M.2 2280 B+M Key form factor, making it suitable for integration into a wide range of edge computing platforms. Its PCIe Gen 3 x2 interface provides high-speed communication between the Hailo-8 accelerator and the host processor.
The module is designed for real-time computer vision and AI inference workloads such as object detection, image classification, intelligent video analytics, industrial visual inspection and multi-camera processing. It supports simultaneous multi-stream and multi-model inference, allowing compatible edge systems to process several video streams or neural networks concurrently.
Hailo-8 supports both x86 and ARM-based host architectures, giving developers flexibility when integrating the module into embedded computers, industrial systems and edge AI platforms. Supported operating systems include Linux and Windows.
The Hailo software ecosystem supports widely used deep-learning frameworks including TensorFlow, TensorFlow Lite, Keras, PyTorch and ONNX. The software suite includes HailoRT, the Hailo Dataflow Compiler and Hailo Model Zoo resources for optimisation, deployment and runtime execution of trained AI models.
The HM218B1C2ZAE is specified for an extended operating temperature range from -40°C to +85°C, making it suitable for industrial automation, transportation, outdoor systems and other demanding edge environments.
As a starter-kit configuration, the product includes thermal-management accessories to assist with evaluation and integration. This makes the HM218B1C2ZAE suitable for developers and system integrators building compact edge AI, machine vision and intelligent video analytics solutions.
Up to 26 TOPS AI inference performance
Typical power consumption of approximately 2.5 W
Manufacturer Part Number: HM218B1C2ZAE
M.2 2280 B+M Key form factor
PCIe Gen 3 x2 host interface
Powered by the Hailo-8 AI processor
Designed for real-time edge AI inference
Supports simultaneous multi-stream processing
Supports multi-model neural-network inference
Compatible with x86 and ARM host processors
Supports Linux and Windows
Compatible with TensorFlow, TensorFlow Lite, Keras, PyTorch and ONNX
Extended operating temperature from -40°C to +85°C
Suitable for industrial and embedded edge systems
Supports machine vision and intelligent video analytics
Suitable for smart cameras, robotics and industrial automation
Compact M.2 design for space-constrained systems
Starter kit includes thermal-management accessories
| Specification | Details |
|---|---|
| Manufacturer | Hailo Technologies |
| MPN | HM218B1C2ZAE |
| Processor | Hailo-8 |
| AI Performance | Up to 26 TOPS |
| Typical Power Consumption | Approx. 2.5 W |
| Module Type | M.2 AI Acceleration Module / Starter Kit |
| Form Factor | M.2 2280 |
| Key | B+M |
| Host Interface | PCIe Gen 3 x2 |
| Host Architecture Support | x86, ARM |
| Operating Systems | Linux, Windows |
| AI Frameworks | TensorFlow, TensorFlow Lite, Keras, PyTorch, ONNX |
| Operating Temperature Min. | -40°C |
| Operating Temperature Max. | +85°C |
| Multi-Stream Processing | Supported |
| Multi-Model Processing | Supported |
| Primary Workload | Deep Learning / Neural Network Inference |
| Deployment Type | Edge / Embedded AI |