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Today, we release DSpark draft model checkpoints for three models from our LFM2.5 family: LFM2.5-1.2B-Instruct, LFM2.5-2.6B, and LFM2.5-8B-A1B. These add a speculative decoding path that trades a minimal memory increase for a large decoding speedup without changing output quality:
Faster inference: up to 3.18 throughput improvement on a GPU and up to 2.87x on-device.
Toward on-device agentic inference: cuts function-calling latency by 57% on average for LFM2.5-2.6B
Day-one support for llama.cpp and SGLang: LFM-compatible DSpark integration is open-sourced upstream
