LFM2.5-Encoders for Fast Long-Context Inference on CPU
Hugging Face Blog
Liquid AI released two encoder models, LFM2.5-Encoder-230M and LFM2.5-Encoder-350M, that match larger models on benchmarks while maintaining fast inference on CPU with 8,192-token context windows. The 230M model achieves 3.7× faster CPU inference than ModernBERT-base at long context, processing 8,192 tokens in 28 seconds versus ModernBERT's 90 seconds. These models enable document-scale classification, routing, and detection tasks to run cheaply on existing hardware without GPU acceleration.
