Hacker Builds Offline Multimodal Raspberry Pi Assistant

Hardware hacker Suhas Telkar recently built an offline multimodal AI assistant that runs on a Raspberry Pi 5 with 4GB RAM, using a quantized Gemma 3 4B Instruct model via llama.cpp. The system handles local speech (Vosk/eSpeak), vision (YOLOv8 Nano), and retrieval-augmented memory (ChromaDB with all-MiniLM-L6-v2 embeddings), generating about 5–10 tokens/sec with first-token latency under eight seconds. Source code is MIT-licensed on GitHub.