Potato OS (github.com)

Potato OS is an experimental Raspberry Pi Linux modification designed for optimized local inference of large language models (LLMs) that runs entirely on-device without relying on cloud resources or GPUs. Compatible with Raspberry Pi 4 and 5 models, it enables users to run quantized models with a user-friendly browser chat interface. The recommended setup utilizes the Pi 5 for a performance of approximately 8 tokens per second, while the Pi 4 operates at about a quarter of that speed. The software allows an automatic download of a starter model upon first boot, enabling an accessible hands-on experience with LLMs starting from an affordable $80 hardware investment. This initiative is significant for the AI/ML community as it democratizes access to advanced machine learning capabilities at a low cost, promoting experimentation and tinkering among developers and enthusiasts. Potato OS facilitates features like multi-chat sessions, model management, and system monitoring, making it a versatile tool for users to engage with AI in real-time. Its dual inference runtime supports various implementations, reflecting a shift towards local processing that could reduce dependence on centralized cloud services, thereby enhancing privacy and efficiency in AI applications. However, it's currently in an early release stage intended for testing, with no over-the-air updates available yet.