LiquidAI's 2.6B model rivals 4x larger models on agentic tasks

LFM2.5 2.6B model competitive with 4x larger models

LiquidAI has released LFM2.5-2.6B, a compact 2.6B-parameter model that competes with models four times its size on agentic workloads like tool use and instruction following. It features a 128K context window, agentic reinforcement learning, and efficient inference, achieving 220 tokens/s on an Apple M5 Max and 113 tokens/s on an AMD Ryzen CPU, all in under 2.5 GB of memory. The model is part of the LFM2.5 family, designed for on-device deployment, and is available in multiple formats for various frameworks.