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Liquid AI releases LFM2.5-24B-A2B, an open-weight model for local agents

On October 13, 2026, Liquid AI released LFM2.5-24B-A2B, a reasoning model with 24B total and about 2.45B active parameters. Weights are on Hugging Face; commercial use has a revenue threshold.

Three rows of bar charts comparing LFM2.5-24B-A2B with Qwen3.6-35B-A3B, Gemma-4-26B-A4B-it and Nemotron-3.5-Lightning on speed and memory
Liquid AI’s edge-inference comparison of prefill, decode speed and memory on Apple M5 Max, Mac Studio and AMD Ryzen AI Max+ 395 (vendor measurements). Source: Liquid AI (Hugging Face model card)

Liquid AI released LFM2.5-24B-A2B on October 13, 2026, calling it the largest and final model in the LFM2.5 family. Base and post-trained versions are available as open weights on Hugging Face and in Liquid’s Playground.

Per the model card, it is a text-only reasoning model with 24B total and 2.45B active parameters, a 131,072-token context and 16 languages including Chinese. Unlike LFM2-24B-A2B, it always reasons before answering. Liquid recommends it for agents that reason, call tools and run locally, and advises pairing it with retrieval or web search rather than using it alone for knowledge-heavy tasks.

Liquid says it is competitive with Qwen3.6-35B-A3B, which has about 50% more total and active parameters, on five of eight agentic and tool-use benchmarks, for example 48.09 versus 38.19 on LiveClaw. The company reports 184 decode tokens per second on an Apple M5 Max, and over 21,000 aggregate output tokens per second on one NVIDIA B300 under sustained concurrent load with SGLang 0.5.22, BF16, 1,024 input and up to 256 output tokens. Both are vendor measurements; the latter is total concurrent throughput, not single-user speed.

Formats include GGUF (llama.cpp), MLX, FP8 and ONNX; a DSpark draft model for SGLang speculative decoding is listed as coming soon. Through Liquid’s own API it costs $0.10 per million input tokens ($0.05 cached) and $1.00 per million output tokens, with $2 in credit for new sign-ups.

The weights use the LFM Open License v1.0, based on Apache 2.0 but with a commercial-use limit: the license text defines the threshold as annual revenue of $10 million or more, above which companies must buy a commercial license. Qualified nonprofits using it for non-commercial or research purposes are not subject to the revenue threshold.

Sources

  1. LFM2.5-24B-A2B (Liquid AI blog) — Liquid AI
  2. LiquidAI/LFM2.5-24B-A2B model card — Liquid AI (Hugging Face)
  3. LFM Open License v1.0 — Liquid AI

Topics:Model · Liquid AI

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