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English(EN) GLM 5.1 Locally: 40tps, 2000+ pp/s

GLM 5.1 在 RTX 6000 Pro 显卡上实现本地 40 tokens/秒

一位 Reddit r/LocalLLaMA 社区用户已成功优化 GLM 5.1 模型以进行本地部署,并取得了令人印象深刻的性能指标。通过对 sglang 推理软件应用特定补丁并使用四块 RTX 6000 Pro GPU,他们报告了 40 tokens/秒 的吞吐量和超过 2000 tokens/秒 的预填充上下文处理速度。用户指出,当前的推理软件尚未针对这些显卡进行完全优化,预示着未来可能实现更高的性能。 AI

影响 展示了通过优化硬件和软件配置实现高吞吐量本地 LLM 推理的潜力。

排序理由 用户报告的在特定硬件上对开源模型的性能优化。

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

GLM 5.1 在 RTX 6000 Pro 显卡上实现本地 40 tokens/秒

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Research
用户报告的在特定硬件上对开源模型的性能优化。
Source corroboration
Single-source cluster
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
model release, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
125 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准

报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/val_in_tech ·

    GLM 5.1 本地部署:40tps,2000+ pp/s

    <!-- SC_OFF --><div class="md"><p>After some sglang patching and countless experiments, managed to get reap-ed nvfp4 version running stable and FAST on 4 x RTX 6000 Pros (limited to 350W). Very happy with performance and quality. Inference software is still under-optimized for th…