Liquid AI released LFM3, a family that puts text, vision, audio, omni and decision models on one shared backbone of roughly 2B parameters, with base and post-trained weights open-weight on Hugging Face and its API. The backbone mixes gated short convolutions, sliding-window attention and global attention, was pre-trained on 22T tokens, and a final 3.5T-token mid-training stage extends context to 256K. Per parameter, LFM3-1.7B matches LFM2-1.2B on short prompts across edge devices and is about 25% faster with 8K tokens in context.
Liquid AI released LFM3, a family that puts text, vision, audio, omni and decision models on one shared backbone of roughly 2B parameters, with base and post-trained weights open-weight on Hugging Face and its API. The backbone mixes gated short convolutions, sliding-window attention and global attention, was pre-trained on 22T tokens, and a final 3.5T-token mid-training stage extends context to 256K. Per parameter, LFM3-1.7B matches LFM2-1.2B on short prompts across edge devices and is about 25% faster with 8K tokens in context.