Unverified50% confidenceFactExact time
The essence of speculative decoding is to predict multiple tokens at low cost and then have the main model verify them in batch; the higher the hit rate, the more valid tokens produced per verification step.
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50%
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Long-term
Relevance
10/10/2026
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Verified投机采样通过小型草稿模型生成候选token由大模型并行验证，可在不损失质量前提下将吞吐提升2-3倍78% similarVerifiedSpeculative decoding submits the candidate sequence generated by the draft model to the target model as a whole for one-shot batch verification, requiring only a single forward pass to determine whether each candidate token is correct.75% similarUnverifiedThe output quality of a model is probabilistic and can only be fully exposed under real traffic distribution, whereas the correctness of code services can be verified in advance through unit tests or integration tests.73% similarVerifiedSpeculative decoding's rejection-sampling-based verification algorithm ensures that the output distribution is exactly equivalent to—rather than merely an approximation of—running the main model alone.72% similarUnverifiedThe actual speedup from speculative decoding is highly dependent on the match between the draft model and the target model, and acceptance rate is the key data for evaluating its effectiveness.71% similar
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