Liquid AI releases LFM3 family of specialized multimodal models built on shared 2B parameter backbone

Liquid AI introduces LFM3, a new generation of Liquid Foundation Models ranging from 1.7B to 2B parameters that unify text, vision, audio, omni, and decision models on a single shared backbone. Key improvements include a tri-hybrid architecture combining short convolutions and attention, enabling LFM3-1.7B to outperform the larger LFM2.5-2.6B with 35% fewer parameters. The text model fits within approximately 1 GB at 4-bit precision and supports a 256K context window for on-device agent deployment. Four specialized model variants -- text, vision, audio, and omni -- are derived from the base model and can be fine-tuned on a single GPU. LFM3-1.7B-Base was pre-trained on 22 trillion tokens, with the final 3.5 trillion tokens focused on agentic traces and tool calls to extend the context window.