LLMInference & InterfacesUpdated 2026.04.28

Speculative Decoding

Also known as추측 디코딩Draft Model추론 가속

In one line

Speculative decoding speeds up inference by letting a small 'draft' model propose several tokens at once and a big model verify them in one shot — a major lever on latency without losing quality.

Going deeper

Speculative decoding lets a small helper model predict several upcoming tokens at once; the big main model then verifies them in a single pass, accepting the matching prefix and regenerating from the first mismatch. Same final output, less wall-clock time. It is one of the standard internal optimisations model vendors use to ship faster inference.

Marketers will not configure it, but it is a big chunk of the answer to 'why does AI keep getting faster?'. Lower latency drives more frequent and longer AI usage, which in turn raises the volume of GEO surface exposure your brand is exposed to.

Recent variants — multi-token prediction, EAGLE, Medusa — push the idea further, and some products lean on it to make streamed responses feel almost instantaneous from the first character.

Related terms

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