Today, we're releasing LFM2.5-8B-A1B , an edge model built for fast, reliable tool calling on consumer hardware. It builds on our LFM2-8B-A1B release from October 2025, with an expanded 128K context window, scaled-up pretraining (from 12T to 38T tokens), and large-scale reinforcement learning. We also doubled its vocabulary to improve tokenization efficiency for non-Latin languages. The result is a model that chains tool calls, achieves tasks, and fits comfortably even on an entry-level laptop. The base (LFM2.5-8B-A1B-Base) and post-trained (LFM2.5-8B-A1B) models are available today on Hugging Face and our Playground . Check out our docs on how to run and fine-tune them locally. *AA-Omniscience Index (higher is better) rewards correct answers and penalizes hallucinations. Scores range from -100 to 100. See more results on Artificial Analysis . Highlights On-device personal assistant. Designed to power real-life applications, chaining tool calls, and following complex instructions on all devices.…