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English(EN) ZFLOW AI improves B300 inference with simulation tuning Testing showed 826 tokens/second peak throughput and lower tail latency using disaggregated serving on D

ZFLOW AI 通过 DeepSeek V4-Pro 调优提升 B300 推理性能

作者 PulseAugur 编辑部 · [1 个来源] ·

ZFLOW AI 通过采用仿真调优，增强了 NVIDIA B300 硬件的推理能力。通过使用 DeepSeek V4-Pro 进行解耦服务，此优化实现了 826 tokens/秒的峰值吞吐量并降低了尾部延迟。 AI

影响 通过先进的服务技术，展示了在专用 AI 硬件上提高推理性能的潜力。

排序理由 这描述了对现有硬件和模型的优化，而不是新发布或基础研究。

在 Mastodon — fosstodon.org 阅读 →

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ZFLOW AI 通过 DeepSeek V4-Pro 调优提升 B300 推理性能

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这描述了对现有硬件和模型的优化，而不是新发布或基础研究。
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
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报道来源 [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    ZFLOW AI 通过模拟调优改进 B300 推理 测试显示使用 D 上的分离式服务可实现 826 token/秒的峰值吞吐量和更低的尾部延迟

    ZFLOW AI improves B300 inference with simulation tuning Testing showed 826 tokens/second peak throughput and lower tail latency using disaggregated serving on DeepSeek V4-Pro. The post ZFLOW AI imp... #Industry #News #NVIDIA #B300 #platform #Simulation #ZFLOW #AI Origin | Interes…

    链接 engineering.com/zflow-ai-improves-b300-in… awakari.com/sub-details.html awakari.com/pub-msg.html

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