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@NVIDIAAI: RL post-training is hitting a rollout bottleneck. This new paper from #NVIDIAResearch shows how speculative decoding in NeMo-RL + @vllm_pr...

@NVIDIAAI 3 信息等级 3 1 噪音/剔除；2 较弱；3 普通事实；4 重要行业动态；5 极重大事件。该分数是信息显著性，不是投资建议。 发布：2026-05-01T20:00 抓取：2026-05-03 15:25
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AI 算力 研究
摘要

NVIDIA Research发布新论文，提出在NeMo-RL结合vLLM中使用推测解码加速强化学习后训练，实现8B模型吞吐量提升1.8倍，235B模型端到端加速2.5倍。

客观事实
  • NVIDIA Research提出推测解码加速RL后训练
  • NeMo-RL+vLLM实现1.8倍吞吐量提升（8B模型）
  • 235B模型端到端加速达2.5倍
NVIDIA NeMo-RL vLLM

原文

RL post-training is hitting a rollout bottleneck.

This new paper from #NVIDIAResearch shows how speculative decoding in NeMo-RL + @vllm_project can accelerate rollouts losslessly, with 1.8x higher throughput at 8B and projected 2.5x end-to-end speedup at 235B.

Read the full paper: https://t.co/twR4LEQNmy

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