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This paper studies predictive flow matching under distribution drift, proposing DyProd-FM which refits on dyadic historical prefixes and uses a sleeping Prod master to achieve minimax-optimal dynamic regret under both relative velocity risk variation and target-law variation, without requiring convexity or curvature assumptions.