Transformers

推測解碼利用草稿模型預測多個詞元，再由目標模型並行驗證。這在特定條件下能減少延遲，但接受率與硬體邊界決定了真實收益。本文拆解核心機制、效能取捨與維運考量。

Speculative decoding uses a draft model to predict multiple tokens, which the target model then verifies in parallel. Under certain conditions, this can reduce latency, but acceptance rate and hardware limits determine the actual gains. This article breaks down the core mechanism, performance trade-offs, and operational considerations.