Speculative decoding eliminates the sequential bottleneck of autoregressive inference by using a highly efficient draft model to propose candidate tokens that your primary target model validates in a single, parallelized forward pass. For production engineers, implementing this technique dramatically reduces generation latency for real-time, multi-turn agentic workflows, but it requires you to manage the additional memory and infrastructure overhead of running two synchronized models simultaneously.