Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI
AWS invented and open-sourced P-EAGLE, parallelizing speculative decoding for up to 1.69x faster LLM inference on SageMaker.
“P-EAGLE instead fills positions 2–4 with learnable placeholders and predicts all four tokens at once”
AWS introduced P-EAGLE, an open-source method that parallelizes speculative decoding by predicting all draft tokens in a single forward pass, eliminating EAGLE's sequential drafting bottleneck. Now natively supported in Amazon SageMaker JumpStart, it delivers up to 1.69x throughput speedup over EAGLE-3. It matters as a concrete inference-optimization advance for enterprise LLM deployments, though it is a vendor-specific engineering improvement rather than an industry-wide signal.