Speculative decoding buys latency with spare compute, and a busy fleet has no spare compute. The speedup formula with acceptance rate and draft cost inside it, the batch size where the gain turns negative, where the draft runs and what it costs, the monitoring that catches a silent regression, and rollout per class.
Updated Sep 2026 · Grounded in real AI infrastructure interview loops and written to a senior-engineer editorial bar, with every number worked and every diagram hand-built.
Speculative decoding buys latency with spare compute, and a busy fleet has no spare compute. The speedup formula with acceptance rate and draft cost inside it, the batch size where the gain turns negative, where the draft runs and what it costs, the monitoring that catches a silent regression, and rollout per class.
Ranked by how closely each one overlaps this question's topic, so the first card is the thing to read if the answer above moved too fast.
Scored on the speedup arithmetic with acceptance rate and draft overhead, on knowing it pays at low batch and hurts at high batch, on draft placement and memory cost, and on per-class rollout with acceptance-rate monitoring as the guard.
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