AnalysisAI ModelsOctober 20, 2026

Explainer: speculative decoding speeds LLMs by shifting GPU work, not cutting it

Read original source →jbarrow.ai

Speculative decoding executes more total FLOPs per sequence, not fewer — a small draft model proposes tokens that the big model verifies in one parallel forward pass. The gain comes from moving the GPU off memory-bound single-token decoding, where all active parameters (e.g. 27B for Qwen3.5-27B) must be streamed per token.

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