Français(FR) datapoint: 2x M5U cluster (GLM/Qwen)

用户分享 GLM 和 Qwen 模型 M5U 集群的性能数据

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-26 14:26

一位用户在 r/LocalLLaMA 上分享了一个双 M5U 集群的性能数据，详细介绍了设置挑战以及 General Language Model (GLM) 和 Qwen 模型的基准测试结果。该用户并非程序员，由于训练数据不足，他依赖 Deepseek 进行设置协助。虽然 GLM 5.3 实现了 4.9k 的预填充速度和 100 token/秒的解码速度，但用户觉得太慢，于是选择了 Qwen Flash Next，后者报告了 8k 的预填充和 200 token/秒的解码速度。 AI

影响为考虑类似硬件设置进行本地 LLM 部署的用户提供了真实的性能见解。

排序理由用户生成的特定硬件和模型的性能数据，并非官方发布或基准测试。

在 r/LocalLLaMA 阅读 →

基础设施

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

本文如何被排名

Signal score: 3 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 用户生成的特定硬件和模型的性能数据，并非官方发布或基准测试。
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: 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: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

r/LocalLLaMA TIER_1 Français(FR) · /u/Viktri1 · 2026-10-26 14:26

datapoint: 2x M5U cluster (GLM/Qwen)

<div class="md"><p>Caveats: IDK how to set anything up and I asked Deepseek to handle it - not enough training data so without specific guides the set up doesn't work well. I'm not a programmer. My previous model was Qwen 3.8 27B q4 using ninfer. Was getting around…

本文如何被排名

报道来源 [1]

datapoint: 2x M5U cluster (GLM/Qwen)

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