Liquid AI's LFM2.5-8B-A1B runs on phones with 1.5B active parameters
Liquid AI released LFM2.5-8B-A1B, an 8-billion-parameter mixture-of-experts model with 1.5 billion active parameters per forward pass, designed for on-device deployment on phones, laptops, and robotics hardware.
Liquid AI released LFM2.5-8B-A1B this week, an 8-billion-parameter mixture-of-experts model that activates only 1.5 billion parameters per forward pass. Built for on-device inference on phones, laptops, and embedded systems, the model ships with 128,000-token context, was pretrained on 38 trillion tokens, and underwent large-scale reinforcement learning tuning. According to Liquid AI, the architecture competes with models three to four times its size on tool calling and reasoning tasks.
The weights are available on HuggingFace under the LFM2 open-weight license, which permits commercial use and derivative fine-tunes. An abliterated GGUF quantization also appeared on the platform, tagged as uncensored and ready for imatrix quantization workflows. The open-weight license makes the model a direct competitor to closed on-device APIs and heavier open-weight alternatives that require datacenter GPUs.



