Hugging Face Blog·· 24 days agoSelectedAI score60
Accelerating vision-language models with LFM2.5-VL-DSpark
Accelerating vision-language models with LFM2.5-VL-DSpark
AI introduction
Liquid AI has released experimental DSpark draft models for the vision-language model LFM2.5-VL-3B, using speculative decoding to trade for faster inference without changing output quality — decoding speeds up to 3.13x on-device and 2.66x on H100, with end-to-end gains up to 2.62x and 2.27x respectively.
Why it matters
The article details a speculative decoding acceleration scheme for vision-language models with concrete speedups and memory overhead, plus integration guidance for llama.cpp, MLX-VLM, and SGLang.
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Source: Hugging Face Blog · huggingface.co