Liquid AI releases LFM2.5-24B-A2B, an open-weight on-device agent model with 2B active params
LFM2.5-24B-A2B is a 24B MoE reasoning model that activates only about 2B parameters per token, with a 131K context window, built for private local agents. Liquid reports strong tool-use scores (including 27.69 on AutomationBench and 48.09 on LiveClaw versus larger Qwen3.6-35B-A3B) and 184 tokens/s on an Apple M5 Max. Base and post-trained weights are on Hugging Face with llama.cpp, MLX, vLLM, and SGLang support.