[GH-ISSUE #7700] 为什么CPU只占用百分之六,但是运行的时候,CPU出力的程度比GPU的程度还高呢?如何更多的让GPU干活呢? #82600

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opened 2026-05-09 15:18:34 -05:00 by GiteaMirror · 3 comments
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Originally created by @fg2501 on GitHub (Nov 16, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/7700

What is the issue?

image
如何使得GPU干活的时候,百分百出力呢?

OS

Windows

GPU

Nvidia

CPU

AMD

Ollama version

0.3.13

Originally created by @fg2501 on GitHub (Nov 16, 2024). Original GitHub issue: https://github.com/ollama/ollama/issues/7700 ### What is the issue? ![image](https://github.com/user-attachments/assets/4522364e-dea7-4ac8-853a-49b63020eeac) 如何使得GPU干活的时候,百分百出力呢? ### OS Windows ### GPU Nvidia ### CPU AMD ### Ollama version 0.3.13
GiteaMirror added the questionneeds more info labels 2026-05-09 15:18:42 -05:00
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@rick-github commented on GitHub (Nov 16, 2024):

如何使得GPU干活的时候,百分百出力呢?

Use a model that fits 100% on the GPU.

<!-- gh-comment-id:2480554589 --> @rick-github commented on GitHub (Nov 16, 2024): > 如何使得GPU干活的时候,百分百出力呢? Use a model that fits 100% on the GPU.
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@fg2501 commented on GitHub (Nov 17, 2024):

如何使得GPU干活的时候,百分百出力呢?

使用一个能够 100%运行在 GPU 上的模型。

大佬,除了这个方法以外,还有其他方法吗?

<!-- gh-comment-id:2480931676 --> @fg2501 commented on GitHub (Nov 17, 2024): > > 如何使得GPU干活的时候,百分百出力呢? > > 使用一个能够 100%运行在 GPU 上的模型。 大佬,除了这个方法以外,还有其他方法吗?
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@rick-github commented on GitHub (Nov 17, 2024):

qwen2.5:14b doesn't need 15GB to run:

$ ollama ps
NAME           ID              SIZE      PROCESSOR    UNTIL   
qwen2.5:14b    7cdf5a0187d5    9.9 GB    100% GPU     Forever    

If you share server logs, we may be able to pinpoint why the model is so large. I suspect num_ctx or OLLAMA_NUM_PARALLEL are larger than usual.

<!-- gh-comment-id:2481187978 --> @rick-github commented on GitHub (Nov 17, 2024): qwen2.5:14b doesn't need 15GB to run: ```console $ ollama ps NAME ID SIZE PROCESSOR UNTIL qwen2.5:14b 7cdf5a0187d5 9.9 GB 100% GPU Forever ``` If you share [server logs](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues), we may be able to pinpoint why the model is so large. I suspect `num_ctx` or `OLLAMA_NUM_PARALLEL` are larger than usual.
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Reference: github-starred/ollama#82600