Liquid AI Releases LFM2.5-VL-3B-DSpark: Speculative Decoding for

Liquid AI Releases LFM2.5-VL-3B-DSpark: Speculative Decoding for Vision-Language Models With Up to 3.13x Faster Decoding

Liquid AI has announced LFM2.5-VL-3B-DSpark, an experimental speculative-decoding draft model for its LFM2.5-VL-3B vision-language model. The drafter adds about 280M parameters and accelerates decoding without changing the model’s output. According to Liquid AI, the release achieves up to 3.13x faster decoding on Apple silicon and up to 2.66x on an NVIDIA H100.

Is It Deployable?

Yes. Weights are live on Hugging Face in Safetensors and GGUF formats, with day-one support in SGLang, MLX-VLM, and llama.cpp. Liquid AI labels the release experimental, and it ships under the LFM Open License v1.0, which allows free commercial use only for companies with under $10M in annual revenue.

What Speculative Decoding Changes for a VLM

A standard model generates one token per forward pass. Speculative decoding adds a small drafter that proposes several tokens ahead. The large target model then checks the whole block in one pass and keeps the tokens it agrees with.

DSpark follows the recipe from Liquid AI’s text-model DSpark drafters, described in the DSpark paper. The drafter reads the target model’s hidden states from several layers and predicts the next k tokens.

The key design point: modality does ...

via MarkTechPost