small language models

Liquid AI has released LFM2.5-2.6B, a 2.6B-parameter model trained on 34 trillion tokens with a 128K context window, built for on-device agentic workloads. The company claims it is competitive with models four times its size on tool use and instruction following.

Liquid AI has released LFM2.5-2.6B, a 2.6B-parameter model designed to run capable tool-calling agents locally on laptops and phones. The company claims it matches or beats models up to 4x its size on instruction-following and tool-use benchmarks while running under 2.5GB of memory.

Liquid AI has released LFM2.5-230M, a 230M parameter hybrid model trained on 19 trillion tokens with a 32,768 token context window. The model achieves 213 tok/s decode speed on Galaxy S25 Ultra and 42 tok/s on Raspberry Pi 5, with support for function calling and data extraction tasks.