Liquid AI Releases LFM2.5-2.6B: An On-Device Agentic Model With 128K Context, Tool Calling, And Open Weights

AI Releases LFM2.5-2.6B: An On-Device Agentic Model With 128K Context, Tool Calling, And Open Weights">

Liquid AI released LFM2.5-2.6B , an agentic model that runs entirely on-device. It plans, calls tools, and works through multi-step tasks on phones, laptops, PCs, and robots. The model has 2.69B total parameters, a 131,072-token context window, and a 128,000-token vocabulary. Pre-training used approximately 34 trillion tokens. Two checkpoints shipped: LFM2.5-2.6B-Base for fine-tuning, and LFM2.5-2.6B post-trained for agentic workloads. Because inference stays local, data never leaves the device and the marginal cost of each run is near zero. Liquid AI reports tool-use and instruction-following scores competitive with models nearly four times its size.

The answer is Yes. Both checkpoints are public on Hugging Face under the lfm1.0 license. Weights ship in native, GGUF , MLX , and ONNX formats, with day-one support in llama.cpp, vLLM, SGLang, and LM Studio.

LFM2.5-2.6B has 2.69B total parameters across 30 layers. The stack is 22 double-gated short convolution blocks plus 8 grouped-query attention blocks. Vocabulary size is 128,000 and context length is 131,072 tokens. Pre-training used approximately 34 trillion tokens.

Liquid AI doubled the vocabulary to 128K by extending the existing tokenizer in place rather than retraining from scratch. A dedicated mid-training phase extends context to 128K. The model covers 16 languages and is text-only.

The base checkpoint becomes an agent through four stages.

Liquid AI compared LFM2.5-2.6B against gemma-4-E2B-it (5.1B), gemma-4-E4B-it (8B), Qwen3.5-4B (4.7B) and Qwen3.5-9B (9.7B).

It leads every instruction-following benchmark reported and nearly every tool use benchmark, trailing Qwen3.5-9B only on BFCLv4. Coding is where larger models keep an edge: LiveCodeBenchv6 is 59.41 versus 69.86 for Qwen3.5-9B.

Check out the Technical details , LFM2.5-2.6B , and LFM2.5-2.6B-Base . Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter . Wait! are you on telegram? now you can join us on telegram as well.

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