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  5. Speculative Decoding
Inference & Deployment

Speculative Decoding

Speculative decoding accelerates generation by using a faster draft process to propose tokens that a target model verifies in groups.

Ask Melo about this← all terms

Accepted proposals allow several output positions to advance with fewer target-model steps, while rejected tokens are corrected according to the verification algorithm. Proper methods preserve the target distribution despite the draft approximation.

Related terms

Inference EngineContinuous BatchingBeam SearchLogitModel VersioningOn-Device Inference

Where Speculative Decoding comes up

  • ForeSpark: Meta-Hosted Code Cuts Wasted Drafting in Speculative Decoding
  • What Is Speculative Decoding? Faster LLM Token Generation Explained
  • Meta TextSeal2: An Open-Source LLM Text Watermark That Survives Speculative Decoding
  • DFlash-MLX Brings Lossless Speculative Decoding to Apple Silicon — Up to ~189 tok/s on M5 Max