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LFM2.5-24B-A2B-GGUF

Provides a GGUF-quantized build of the LFM2.5 24B agent-oriented model for on-device CPU inference with llama.cpp, enabling local text generation and tool-calling workflows; includes a QAD Q4_0 checkpoint and recommended sampling defaults.

LFM2.5-24B-A2B

Runs a 24B-parameter mixture-of-experts reasoning model with only ~2B active parameters per token for fast on-device agentic workflows; provides a 131K-token context and 128K vocabulary, post-trained for tool calling and agentic RL—pair with retrieval for knowledge-heavy tasks.