Liqvid AI Releases LFM2.5-8B-A1B: An Edge MoE Model for Tool Calling on Consumer Hardware
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simjnd
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Summary
Liqvid AI released LFM2.5-8B-A1B, an edge-optimized Mixture-of-Experts model designed for fast, reliable tool calling on consumer hardware. It builds on the October 2025 LFM2-8B-A1B release with an expanded 128K context window, scaled-up pretraining from 12T to 38T tokens, large-scale reinforcement learning, and a doubled vocabulary for improved tokenization efficiency in non-Latin languages. The model fits comfortably on entry-level laptops and is available on Hugging Face.
Key quotes
· 5 pulledToday, 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.
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