Inference
Speculative Decoding
An inference technique where a small, fast draft model proposes several tokens ahead and the large target model checks them all in one parallel forward pass.
In depth
An inference technique where a small, fast draft model proposes several tokens ahead and the large target model checks them all in one parallel forward pass. Tokens the target model agrees with are kept, and the first rejected one is resampled, so the output distribution is identical to running the large model alone. The original paper reported 2-3x speedups on T5-XXL without retraining or architecture changes. It works best when the draft model guesses well, such as on predictable code or boilerplate.
Primary source: arxiv.org
Example
It works best when the draft model guesses well, such as on predictable code or boilerplate.
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FAQ
Common questions
What is Speculative Decoding?
An inference technique where a small, fast draft model proposes several tokens ahead and the large target model checks them all in one parallel forward pass.
Why does Speculative Decoding matter for AI developers?
Speculative Decoding sits in the Inference part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Speculative Decoding?
Developers Digest publishes tutorials and videos that cover Inference topics including Speculative Decoding. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Inference
Input vs Output Token Pricing
The split pricing model where LLM APIs charge one rate per million tokens you send (input) and a higher rate per million tokens the model generates (output).
Inference
Multi-Token Prediction (MTP)
A training objective where a language model learns to predict the next several tokens at each position instead of only the next one, using extra output heads on a shared model trunk.
Inference
Prefill
The first phase of LLM inference, where the model processes the entire input prompt in parallel and builds the KV cache before producing any output.
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