# Liquid AI releases six LFM3 models for on-device specialization > Source: > Published: 2026-10-27 23:37:19+00:00 # Liquid AI releases six LFM3 models for on-device specialization **The shared-base family covers text, vision, audio and decision tasks. Liquid AI says each model can be fine-tuned on a single GPU, and its checkpoints are available on Hugging Face.** By [Ryan Merket](https://runtimewire.com/author/ryan-merket) · Published Primary source: [Hugging Face Newsroom](https://huggingface.co/blog/LiquidAI/lfm3) ## Why it matters LFM3 puts Liquid AI's device-first strategy into a developer-facing model family: shared foundations, task-specific fine-tuning and local deployment. Whether that translates into customer adoption depends on performance in real workloads, not the company's benchmark claims alone. [Ramin Hasani](https://www.liquid.ai/team/ramin-hasani?ref=runtimewire) ([@ramin_m_h](https://x.com/ramin_m_h?ref=runtimewire)), the co-founder and CEO of [Liquid AI](https://www.liquid.ai/?ref=runtimewire), has spent years making the case that useful AI should not have to live in a data center. On October 27th, Liquid AI published [its LFM3 announcement on Hugging Face](https://huggingface.co/blog/LiquidAI/lfm3?ref=runtimewire): six text, vision, audio, omni and decision models built from a shared base and designed for further specialization. The announcement was published that day.… When you purchase through links in our articles, [we may earn a small commission](https://runtimewire.com/affiliate-monetization-standards). This doesn’t affect our editorial independence.