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GLM 5.1 achieves 40 tokens/sec locally on RTX 6000 Pro cards

A user on the r/LocalLLaMA subreddit has successfully optimized the GLM 5.1 model for local deployment, achieving impressive performance metrics. By applying specific patches to the sglang inference software and utilizing four RTX 6000 Pro GPUs, they reported a throughput of 40 tokens per second and over 2000 tokens per second for prefilled contexts. The user noted that the current inference software is not fully optimized for these cards, suggesting further performance gains are possible. AI

IMPACT Demonstrates potential for high-throughput local LLM inference with optimized hardware and software configurations.

RANK_REASON User-reported performance optimization of an open-source model on specific hardware.

Read on r/LocalLLaMA →

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

GLM 5.1 achieves 40 tokens/sec locally on RTX 6000 Pro cards

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Research
User-reported performance optimization of an open-source model on specific hardware.
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
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
153 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

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

    GLM 5.1 Locally: 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…