Speculative Decoding: 3× Faster LLM Inference with Zero Quality Loss

Speculative decoding is one of the most important performance optimizations in modern LLM serving—and most people still don’t understand how it really works. In this video, we break down speculative decoding step by step, starting from standard autoregressive decoding and showing how a fast draft model and a target model work together to cut inference time by up to 3× with no loss in output quality. You’ll learn why speculative decoding is mathematically lossless, how token acceptance and rejection guarantees identical sampling, and how real systems achieve these speedups in practice. We the…