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User shares M5U cluster performance data for GLM and Qwen models

By PulseAugur Editorial · [1 sources] ·

A user on r/LocalLLaMA shared performance data for a dual M5U cluster, detailing setup challenges and benchmark results for General Language Model (GLM) and Qwen models. The user, not a programmer, relied on Deepseek for setup assistance due to insufficient training data. While GLM 5.3 achieved a prefill speed of 4.9k and 100 tokens/sec decode, the user found it too slow and opted for Qwen Flash Next, which reported an 8k prefill and 200 tokens/sec decode. AI

IMPACT Provides real-world performance insights for users considering similar hardware setups for local LLM deployment.

RANK_REASON User-generated performance data for specific hardware and models, not an official release or benchmark.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

User shares M5U cluster performance data for GLM and Qwen models

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3 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
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Tool
User-generated performance data for specific hardware and models, not an official release or benchmark.
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 Français(FR) · /u/Viktri1 ·

    datapoint: 2x M5U cluster (GLM/Qwen)

    <!-- SC_OFF --><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…

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