AWS shows how P-EAGLE speculative decoding can accelerate SageMaker endpoints

AWS has published a guide to using P-EAGLE speculative decoding directly within Amazon SageMaker AI. The walkthrough covers model selection, parallel drafting configuration, and deployment of a real-time endpoint.

Speculative decoding matters because inference speed and cost remain major constraints for generative AI applications. By drafting and verifying tokens more efficiently, teams can improve responsiveness without changing the user-facing model behavior.

The guide is aimed at practitioners trying to squeeze more performance from production endpoints as AI usage grows.