Show Notes
Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode! Liquid AI’s LFM3 family shows how far tiny local models have come. A 1.7B-parameter model can now code, edit files, run lightweight AI agent tasks, understand images and voice, and even run fully offline on low-cost hardware. We’ll talk about: LFM3 1.7B: How a tiny local model handled coding, file editing, research, and agent workflows on a regular laptop. Vision + OCR: Where LFM3 did well with images, manuals, and extracting structured information. Offline Voice + Video: What worked with audio and multimodal understanding — and where hallucinations still showed up. $80 Arduino Test: How a 4-bit LFM3 model ran on just 4GB of RAM at around 3 tokens per second. Who It’s For: Why small local models could make private AI agents and offline assistants much more accessible. Keywords: Liquid AI, LFM3, Local LLM, LFM3 1.7B, Offline AI, AI Agents, Hermes Agent, Arduino Uno Q, Edge AI, Local AI, Multimodal AI, Vision Model, Voice AI, Small Language Models. Links: Newsletter: Sign up for our FREE daily newsletter. Our Community: Get 3-level AI tutorials across industries. Join AI Fire Academy: 500+ advanced AI workflows ($14,500+ Value)
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