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English(EN) Running Qwen 3.5 35B A3B-Q8_0 gguf on a cheap radeon 7600 at 18 token/s

Qwen 3.6 35B模型在Radeon 7600 GPU上以21 token/秒的速度运行

作者 PulseAugur 编辑部 · [3 个来源] ·

Reddit用户在r/LocalLLaMA子版块分享了他们使用GGUF格式的Qwen 3.6 35B模型在Radeon 7600显卡上运行的经验。在超频VRAM并使用llama.cpp优化设置后，他们达到了每秒21个token的速度。用户还注意到一个奇怪的bug，即当应用程序窗口可见时，token生成速度会降低，而最小化时则会提高。 AI

影响 展示了在消费级硬件上运行大型语言模型可实现的性能。

排序理由 用户在特定硬件和软件上运行特定模型的性能报告。

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

Qwen 3.6 35B模型在Radeon 7600 GPU上以21 token/秒的速度运行

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用户在特定硬件和软件上运行特定模型的性能报告。
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model release
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报道来源 [3]

  1. Towards AI TIER_1 English(EN) · Gian Luca Bailo, Ph.D. ·

    Qwen3.8–27B 在两块中端 GPU 上，发布日实测

    <h4><em>Everyone will publish the benchmark scores. Here is a less glamorous and more useful question: what does it actually cost to run on a home machine — and why that number is not up for negotiation.</em></h4><figure><img alt="Illustration of an open-frame desktop PC on a des…

  2. r/LocalLLaMA TIER_1 English(EN) · /u/Sweaty_Perception655 ·

    在廉价的 radeon 7600 上以 18 token/s 运行 Qwen 3.6 35B A3B-Q8_0 gguf * 更新后提升至 21 t/s

    <!-- SC_OFF --><div class="md"><blockquote> <p><a href="https://www.reddit.com/r/LocalLLaMA/?f=flair_name%3A%22Discussion%22"></a>I also have 64 gb ddr4 ryzen 5600 Using llama.cpp Ubuntu distro</p> <p>Settings are as follows</p> <p>--n-gpu-layers 999 \</p> <p>--n-cpu-moe 36 \</p>…

  3. r/LocalLLaMA TIER_1 English(EN) · /u/Sweaty_Perception655 ·

    在廉价的Radeon 7600上以18 token/s运行Qwen 3.5 35B A3B-Q8_0 gguf

    <!-- SC_OFF --><div class="md"><p>I also have 64 gb ddr4 ryzen 5600 Using llama.cpp Ubuntu distro</p> <p>Settings are as follows</p> <p>--n-gpu-layers 999 \</p> <p>--n-cpu-moe 37 \</p> <p>--no-mmap \</p> <p>-ctk q8_0 \</p> <p>-ctv q8_0 \</p> <p>-fa 1 \</p> <p>-c 9000 \</p> </div>…

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