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 .

💻 Demos : Try LFM2.5-2.6B's agentic capabilities in a Hugging Face space without any setup: Research Agent in your browser : helps you research a specific question and generates a summary

🗒️ Model Details

Model Parameters Description

LFM2.5-2.6B-Base 2.6B Pre-trained base model for fine-tuning

LFM2.5-2.6B 2.6B Post-trained for agentic workloads

LFM2.5-2.6B is a general-purpose text-only model with the following…