Liquid AI

Liquid AI releases a reasoning model built for local agents.

LFM2.5-24B-A2B has downloadable weights. The model card, memory needs and license deserve a closer look.

Source published 2026-10-13Release briefing and editorial analysisAI geeksAI-assisted editorial

Sources checked 2026-10-14. Access and availability can change.

What is available

Liquid AI announced LFM2.5-24B-A2B on October 13. It is a text-only model built for reasoning and tool use. Its detailed model card lists 24 billion total parameters and 2.45 billion active parameters, with a context window of up to 131,072 tokens.

Official weights and compressed versions are listed on Hugging Face. The Q4_K_M file alone is 14.5 GB; that is a download size, not the complete memory requirement for running the model.

Read the speed result carefully

Liquid reports 184 generated tokens per second on an Apple M5 Max using llama.cpp, Q4_K_M and a 4K-token input. This is the developer’s measurement under those conditions, not our test or a speed promise for every Mac. Liquid also advises against relying on the model alone for knowledge-heavy tasks.

Check the license

The repository uses the custom LFM Open License v1.0. Commercial permissions include a $10 million annual-revenue threshold; redistribution and attribution conditions also apply. Read the linked terms for your intended use. Downloadable weights do not mean unrestricted use.

Our take for AI geeks

Editorial analysis: consider a narrowly scoped local experiment after checking your hardware’s capacity. Use invented data and tools limited to reading, then assess correctness, memory use and time to a finished answer. Running the model on your own computer can avoid a hosted model’s per-request charge, but hardware, power and maintenance still cost money. Serving many visitors still requires capacity. We have not downloaded or tested this model.

Sources & further reading

Open the source to check the original wording and current availability.

This is a source-linked briefing, not a hands-on product review. Provider claims and outside evaluations are identified in the text.

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