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The Hailo-10H M.2 AI Acceleration Module (HM22HB2C2XBE) delivers up to 40 TOPS INT4 / 20 TOPS INT8 of on-device AI performance in a compact M.2 2242 Key M form factor with 4GB LPDDR4/4X memory. Using a PCIe Gen 3.0 x4 interface, this industrial-grade edge AI accelerator is designed for generative AI, computer vision, LLMs, VLMs, video analytics and other advanced AI workloads at the edge..
The Hailo-10H M.2 AI Acceleration Module HM22HB2C2XBE is a high-performance edge AI accelerator starter kit designed for systems that require local processing of demanding generative AI and computer vision workloads.
Powered by the Hailo-10H AI processor, the module delivers up to 40 TOPS with INT4 workloads and 20 TOPS with INT8 workloads. This processing capability enables advanced neural networks to run directly on edge systems with reduced dependence on cloud infrastructure.
The HM22HB2C2XBE variant uses a compact M.2 2242 Key M form factor and includes 4GB of LPDDR4/4X memory on the module. The dedicated memory interface allows the Hailo-10H platform to support larger neural-network models and generative AI applications that require more memory than conventional vision-only accelerators.
Host communication is provided through a PCIe Gen 3.0 x4 interface, offering high-speed data transfer between the accelerator and the host processor. The module supports x86 and ARM-based host architectures, allowing it to be integrated into industrial PCs, embedded computers, edge servers and other compatible AI platforms.
Hailo-10H is specifically designed to handle both vision AI and generative AI workloads. Typical use cases include large language models, vision-language models, Stable Diffusion-type applications, intelligent video analytics, computer vision, smart assistants and advanced embedded AI applications.
The module uses Hailo's second-generation structure-driven dataflow architecture, designed to efficiently distribute neural-network operations across the accelerator. This enables high AI compute performance while maintaining low power consumption.
Typical power consumption is approximately 2.5 W, making the Hailo-10H suitable for edge systems where power efficiency and thermal management are important design considerations.
The Hailo software ecosystem supports widely used AI frameworks including TensorFlow, TensorFlow Lite, Keras, PyTorch and ONNX. Supported operating systems include Linux, Windows and Android, providing developers with flexibility when deploying AI applications across different edge platforms.
The industrial-grade Hailo-10H M.2 platform supports an operating temperature range of -40°C to +85°C, making it suitable for industrial automation, smart infrastructure, transportation systems, robotics and other demanding edge environments.
By performing inference locally, the HM22HB2C2XBE can help reduce network latency, bandwidth requirements and reliance on cloud-based AI services while supporting responsive, private and continuously available AI applications.
Up to 40 TOPS INT4 AI performance
Up to 20 TOPS INT8 AI performance
Manufacturer Part Number: HM22HB2C2XBE
Powered by the Hailo-10H AI processor
Compact M.2 2242 Key M form factor
Integrated 4GB LPDDR4/4X memory
PCIe Gen 3.0 x4 host interface
Typical power consumption of approximately 2.5 W
Designed for generative AI and computer vision
Supports large language models
Supports vision-language models
Suitable for image-generation and multimodal AI workloads
Second-generation Hailo neural-network architecture
Supports simultaneous multi-model processing
Compatible with x86 and ARM host architectures
Supports Linux, Windows and Android
Compatible with TensorFlow, TensorFlow Lite, Keras, PyTorch and ONNX
Industrial operating temperature from -40°C to +85°C
Designed for low-latency edge inference
Helps reduce cloud dependency and bandwidth requirements
Standard M.2 interface simplifies system integration
| Specification | Details |
|---|---|
| Manufacturer | Hailo Technologies |
| MPN | HM22HB2C2XBE |
| Processor | Hailo-10H |
| AI Performance INT4 | Up to 40 TOPS |
| AI Performance INT8 | Up to 20 TOPS |
| Module Type | M.2 AI Acceleration Module / Starter Kit |
| Form Factor | M.2 2242 |
| Key | M |
| On-Module Memory | 4GB LPDDR4/4X |
| Host Interface | PCIe Gen 3.0 x4 |
| Host Architecture Support | x86, ARM |
| Operating Systems | Linux, Windows, Android |
| AI Frameworks | TensorFlow, TensorFlow Lite, Keras, PyTorch, ONNX |
| Typical Power Consumption | Approx. 2.5 W |
| Operating Temperature Min. | -40°C |
| Operating Temperature Max. | +85°C |
| Primary Workload | Generative AI / Vision AI / Neural Network Inference |
| Deployment Type | Edge / Embedded AI |