The Raspberry Pi’s latest AI HAT+ 2 expansion is a significant boost for the Raspberry Pi 5, featuring 8 GB of on-board RAM and the Hailo-10H neural network accelerator designed specifically for AI applications. This makes it a powerful tool for those interested in running local AI computing tasks.

Offering up to 40 TOPS (INT4) of inference performance, the AI HAT+ 2 is equipped to handle large language models (LLMs), vision language models (VLMs), and various other generative AI functions with ease. Despite its impressive specifications on paper, the new AI HAT+ 2 delivers computer vision capabilities comparable to its predecessor at 26 TOPS (INT4).

The device connects to the Raspberry Pi via the GPIO connector and utilizes the PCIe interface for communication. Active cooling is recommended due to the high thermal output. It’s compatible with the Raspberry Pi OS and supports tools such as ‘rpicam-apps’ for seamless AI hardware integration.

In testing, the AI HAT+ 2 performed optimally using Docker and the hailo-ollama server with the Qwen2 model, demonstrating efficient operation on the Raspberry Pi platform.

Although the 8 GB RAM is listed as a notable feature, it may not be sufficient for memory-intensive AI applications, especially compared to larger, cloud-based solutions managed by industry giants. However, for edge computing applications requiring local processing, the AI HAT+ 2 provides a balanced solution.

Ultimately, for developers needing superior LLM performance without cloud reliance, the AI HAT+ 2 offers a compelling option—despite the availability of alternative hardware setups with higher memory capacities.