MLX-VLM
AssessTools
An Apple Silicon-oriented toolkit for running vision-language models with MLX.
Why it's here
Placed in Assess: 1 article(s) of evidence from 1 source(s), led by model releases, with 1 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 7Hugging Face Blog·9/24/2026model_releaseLiquidAI releases DSpark draft model for LFM2.5-VL-3B
LiquidAI released an experimental DSpark drafter for its vision-language model LFM2.5-VL-3B, adding speculative decoding to speed up inference without changing output quality. The company reports decode speedups of up to 3.13x on-device and 2.66x on H100, with end-to-end gains up to 2.62x and 2.27x, and day-one support in llama.cpp, MLX-VLM, and SGLang.