Liquid AI reveals 8B-A1B MoE trained on 38T
Liquid AI has launched the LFM2.5-8B-A1B model, which is designed for efficient tool calling on consumer hardware. This new model features an expanded context window and a significantly larger vocabulary, improving its performance on various tasks. It is available for use on platforms like Hugging Face and offers enhanced reasoning capabilities compared to its predecessor.
- ▪The LFM2.5-8B-A1B model has a context window expanded from 32,768 to 128,000 tokens.
- ▪Its vocabulary size has doubled to 128,000 to better support non-Latin languages.
- ▪The model is designed to perform well on both CPU and GPU inference, making it accessible for entry-level laptops.
Opening excerpt (first ~120 words) tap to expand
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.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Liquid.
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