SpecQuant: training-free speculative decoding with multi-quantization yields 35-43% speedups
saurabhtwq · x · 2026-09-21
SpecQuant (on arXiv) is a training-free framework combining speculative decoding with multi-parent quantization: it derives INT4/FP8/FP16 variants from one shared base model and routes queries by predicted complexity — light variants for simple factual tasks, full precision for hard reasoning or long context. On Qwen2.5-based models it shows 35-43% speedups on MMLU, AlpacaEval and GSM8K with <2% accuracy degradation, enabling practical on-device LLM deployment. Authors note experiments date back about a year.
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