LFM2.5
### TL;DR
LFM2.5 is a new generation of small foundation models built on the LFM2 architecture, optimized for on-device and edge deployments. The model family includes variants such as LFM2.5-1.2B-Base, LFM2.5-1.2B-Instruct, and extends to Japanese, vision language, and audio language models. It is released as open weights on Hugging Face and exposed through the LEAP platform.
Key Insights & Metrics
Key Features
- Hybrid LFM2 architecture designed for fast and memory-efficient inference on CPUs and NPUs
- Extended pretraining from 10T to 28T tokens
- Supervised fine-tuning, preference alignment, and large-scale multi-stage reinforcement learning for instruction following, tool use, math, and knowledge reasoning
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