From the source
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.
What changed since LFM2-8B-A1B Compared to LFM2-8B-A1B, this new version expands the context window from 32,768 to 128,000 tokens .
This allows the model to process longer documents and reason for longer.
Its vocabulary size was also scaled up from 65,536 to 128,000 to tokenize non-Latin scripts more efficiently .
We see particularly strong compression gains in Hindi, Thai, Vietnamese, Indonesian, and Arabic.
