Liquid AI Ships DSpark Draft Model, Speeding Up LFM2.5-VL-3B Decoding Up to 3.13x
JosephJacks_ · x · 2026-09-25
Liquid AI released an experimental DSpark draft model bringing speculative decoding to its LFM2.5-VL-3B vision-language model: a lightweight drafter proposes multiple tokens ahead, verified by the target model in a single pass, with no change to output quality.
Benchmarked across six vision-language task categories at batch size 1 and temperature 0:
- MLX on M5 Max: up to 3.13x faster decoding, 2.62x end-to-end
- llama.cpp on M3 Ultra: up to 2.14x faster decoding, 1.77x end-to-end
- SGLang on H100: up to 2.66x faster decoding, 2.27x end-to-end
All results were collected with Pipette, the benchmarking infrastructure behind Liquid AI's public evaluations.
Related event: Liquid AI's DSpark Speculative Decoding Speeds Up VL Model 3.13x(4 posts)→
More from Infra
- Gas-for-AI-datacenters forum co-located with CoRL shows energy demand spillover — carlosdponx · 2026-11-12
- a16z podcast: Mike Volpi on Cisco's 70+ acquisition playbook and the AI buildout — a16z · 2026-11-12
- AMD to pass Intel in server revenue by mid-2027 as share gains 6 points a year — BenBajarin · 2026-11-12
- Study: Reflective Data Center Roofs Actually Cool Daytime Ground by 1.8-2.2°C — SumitGup · 2026-11-12
- Tsinghua's BaGuaLu-2 tames MoE expert-load spikes at runtime, accepted to SC26 — jiqizhixin · 2026-11-12
- antirez backs low-bit DeepSeek 4.1 Flash over Qwen 27B dense on Apple M5 Macs — antirez · 2026-11-12