AI HAT+ 2 upgrades the AI HAT+ platform to 40 TOPS performance using the Hailo-10H accelerator and 8GB onboard RAM. Previous AI HAT+ options offered 13 TOPS (Hailo-8L) and 26 TOPS (Hailo-8). The new board enables local execution of large language models, vision-language models and other generative AI workloads independent of the Raspberry Pi 5. Vision-based tasks like object recognition and pose estimation run at about 26 TOPS, comparable to the Hailo-8 model. Transitioning from earlier AI HAT+ models is reported to be mostly seamless. Hailo provides GitHub resources to support generative AI development on the board.
"If you're into Raspberry Pi computers and AI, then chances are that you're already using the AI HAT+ that was released back in 2024. This was a game-changer in terms of offloading AI workloads onto the Pi 5. The idea is that this is a low-cost, data-private way to process edge AI workloads without needing to use third-party cloud-based AI services. Well, today sees that board get a significant upgrade with the release of the AI HAT+ 2."
"The AI HAT+ came in two versions -- a standard 13 TOPS (tera-operations per second) version powered by a Hailo-8L AI accelerator chip, and a 26 TOPS version powered by the Hailo-8 AI accelerator. The new AI HAT+ 2 boosts this performance to 40 TOPS thanks to the use of the Hailo-10H chip backed up by 8GB of onboard RAM."
"This performance boost allows the AI HAT+ 2 to handle large language models (LLMs), vision-language models (VLMs), and other generative AI workloads locally, independent from the Raspberry Pi 5 board. It can also handle vision-based AI workloads such as object recognition and pose estimation at about the same 26 TOPS performance as that of the Hailo-8-powered AI HAT+. Those who have already built projects around the AI HAT+ and want to take advantage of the performance boost that the AI HAT+ 2 has to offer, fear not, because according to Naush Patuck, Senior Principal Engineer at Raspberry Pi, "transitioning to the AI HAT+ 2 is mostly seamless and transparent.""
Read at ZDNET
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