LFM2.5-2.6B is part of LFM2.5, a family of hybrid models designed for on-device deployment . It builds on the LFM2 architecture with a 128K context window and agentic post-training. Best-in-class agent : Competitive with models 4x larger on tool use, instruction following, and multi-step agentic tasks. Agentic reinforcement learning : Trained inside the most popular agentic harnesses to improve compatibility. Efficient inference : 220 tok/s on an Apple M5 Max and 113 tok/s on an AMD Ryzen CPU, in under 2.5 GB of memory. Find more information about LFM2.5-2.6B in our blog post .…