SGLang 优化 NVIDIA Vera Rubin 推理性能
精选理由
SGLang 优化了 NVIDIA Vera Rubin 的推理性能，还支持强化学习训练，性能提升明显。
SGLang 为 NVIDIA Vera Rubin 带来优化推理，在注意力机制、MoE 和 Kimi K3 NVFP4 的推测验证方面实现性能提升。Miles 进一步实现端到端强化学习训练，使用 SGLang 进行 rollout 并在 Vera CPU 上运行并发智能体沙箱。团队分享了早期结果、基准测试和背后的工程技术。
原文 · LMSYS Org (SGLang)
SGLang brings optimized inference to @nvidia Vera Rubin, with performance gains across attention, MoE, and speculative verification for Kimi K3 NVFP4.
Miles by @radixark takes this further with end-to-end RL training, using SGLang for rollouts and the Vera CPU for concurrent agent sandboxes.
The teams share their early results, benchmarks, and the engineering behind them 👇
