Speculative decoding introduces numerical noise that shifts output distributions in long-horizon tasks. Testing frontier open-weight models reveals that draft acceptance rates can change reasoning accuracy after 30 steps, suggesting speculative decoding is not just a systems optimization but a behavioral modifier.
HOW THIS AFFECTS YOU
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builderOptimizing for speed via draft models may inadvertently degrade agent reasoning performance.
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researcherYou must account for distribution shifts when evaluating speculative decoding in agentic workflows.