Lesson 1355 of 2116
Speculative Decoding for Faster LLM Inference
How speculative decoding speeds up inference using a small draft model.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2speculative decoding
- 3draft model
- 4verification
Concept cluster
Terms to connect while reading
Section 1
The premise
Speculative decoding can 2-3x inference throughput when configured well.
What AI does well here
- Use a small fast model to draft tokens for a large verifier.
- Maintain identical output distribution to the target model.
- Trade GPU memory for latency.
What AI cannot do
- Help when the draft model has poor agreement with the target.
- Improve quality — only speed.
Key terms in this lesson
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