---
title: "Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI"
slug: "parallelize-speculative-decoding-with-p-eagle-on-amazon-sagemaker-ai"
date: 2026-06-16
category: tech-pub
tags: [amazon]
language: en
sources_count: 1
featured: false
publisher: AInauten News
url: https://news.ainauten.com/en/story/parallelize-speculative-decoding-with-p-eagle-on-amazon-sagemaker-ai
---

# Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI

**Published**: 2026-06-16 | **Category**: tech-pub | **Sources**: 1

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## TL;DR

- AWS shows P-EAGLE inside Amazon SageMaker AI: speculative decoding drafts multiple future tokens in parallel instead of one after another, reducing the latency cost of deeper speculation.

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## Summary

- AWS shows P-EAGLE inside Amazon SageMaker AI: speculative decoding drafts multiple future tokens in parallel instead of one after another, reducing the latency cost of deeper speculation.
- JumpStart initially supports four models with pretrained P-EAGLE heads: GPT-OSS-120B, GPT-OSS-20B, Qwen3-Coder-30B-A3B-Instruct, and Gemma-4-31B-IT.
- In AWS-run tests on Qwen3-Coder-30B-A3B-Instruct using NVIDIA B200 GPUs and FP8, P-EAGLE delivers up to 1.69x higher throughput than EAGLE-3 and much more than baseline inference.

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## Why it matters

AWS shows P-EAGLE inside Amazon SageMaker AI: speculative decoding drafts multiple future tokens in parallel instead of one after another, reducing the latency cost of deeper speculation.

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## Key Points

- AWS shows P-EAGLE inside Amazon SageMaker AI: speculative decoding drafts multiple future tokens in parallel instead of one after another, reducing the latency cost of deeper speculation.
- JumpStart initially supports four models with pretrained P-EAGLE heads: GPT-OSS-120B, GPT-OSS-20B, Qwen3-Coder-30B-A3B-Instruct, and Gemma-4-31B-IT.
- In AWS-run tests on Qwen3-Coder-30B-A3B-Instruct using NVIDIA B200 GPUs and FP8, P-EAGLE delivers up to 1.69x higher throughput than EAGLE-3 and much more than baseline inference.

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## Nauti's Take

This is a classic infrastructure post with a real technical core and plenty of vendor framing. P-EAGLE targets a real bottleneck: EAGLE becomes less attractive when deeper speculation adds sequential drafting overhead. The interesting move is that AWS is pushing the optimization into the managed deployment path instead of leaving it as a paper or GitHub demo. Teams already on SageMaker should test it; teams outside AWS should first ask the economic question: does the extra throughput save more money than the managed stack costs?

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## FAQ

**Q:** What is Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI about?

**A:** - AWS shows P-EAGLE inside Amazon SageMaker AI: speculative decoding drafts multiple future tokens in parallel instead of one after another, reducing the latency cost of deeper speculation.

**Q:** Why does it matter?

**A:** AWS shows P-EAGLE inside Amazon SageMaker AI: speculative decoding drafts multiple future tokens in parallel instead of one after another, reducing the latency cost of deeper speculation.

**Q:** What are the key takeaways?

**A:** AWS shows P-EAGLE inside Amazon SageMaker AI: speculative decoding drafts multiple future tokens in parallel instead of one after another, reducing the latency cost of deeper speculation.. JumpStart initially supports four models with pretrained P-EAGLE heads: GPT-OSS-120B, GPT-OSS-20B, Qwen3-Coder-30B-A3B-Instruct, and Gemma-4-31B-IT.. In AWS-run tests on Qwen3-Coder-30B-A3B-Instruct using NVIDIA B200 GPUs and FP8, P-EAGLE delivers up to 1.69x higher throughput than EAGLE-3 and much more than baseline inference.

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## Related Topics

- [amazon](https://news.ainauten.com/en/tag/amazon)

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## Sources

- [Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI](https://aws.amazon.com/blogs/machine-learning/parallelize-speculative-decoding-with-p-eagle-on-amazon-sagemaker-ai/) - AWS Machine Learning Blog

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## About This Article

This article is a synthesis of 1 sources, curated and summarized by AInauten News. We aggregate AI news from trusted sources and provide bilingual (German/English) coverage.

**Publisher**: [AInauten](https://www.ainauten.com) | **Site**: [news.ainauten.com](https://news.ainauten.com)

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*Last Updated: 2026-06-17*