Liquid AI Releases LFM2.5-24B-A2B for Local AI Workflows
Liquid AI released LFM2.5-24B-A2B on Oct. 13, introducing an open-weight reasoning model designed to run AI agents locally on laptops and other supported hardware. For IT teams, it offers another way to automate tasks while keeping model inference on their own equipment.
The model has 24 billion parameters but activates approximately 2.45 billion per token, reducing the computation needed to generate responses. That does not give it the memory requirements of a 2-billion-parameter model.
The release completes the LFM2.5 family, which ranges from 230 million to 24 billion parameters. Both the base and post-trained versions are available on Hugging Face, allowing developers to download, customize and deploy the models. LFM2.5-24B-A2B builds on its predecessor with a context window expanded from 32,768 to 131,072 tokens. The company says its vocabulary expands to 128,000 tokens, improving tokenization for non-Latin languages.
Liquid AIincreased pretraining from approximately 17 trillion to 33 trillion...
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