Unverified50% confidenceFactExact time
dSpark speculative decoding adds a "confidence head" to the drafter, truncating low-confidence candidates early, improving cluster speed by 4% to 7% without sacrificing accuracy.
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10/25/2026
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Related Claims
UnverifiedDSpark 在不改变模型原生能力、不损耗输出质量的前提下，压缩推理响应时延、降低算力消耗、提升硬件承载上限69% similarUnverifiedSpeculative decoding can achieve several-fold improvements in inference throughput when the draft acceptance rate is high.69% similarUnverifiedSpeculative decoding rapidly generates candidate tokens via a small draft model and then has the main model verify them in parallel, typically achieving a 2–4× speedup, with outputs that are mathematically equivalent to those produced without it and no loss in precision67% similarUnverifiedDSA稀疏注意力不仅更快，在某些任务上甚至更准，因为跳过无关token让模型更专注于有效信息67% similar
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