[GH-ISSUE #7794] llama3.2-vision:90b unquantized? #67037

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opened 2026-05-04 09:18:43 -05:00 by GiteaMirror · 2 comments
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Originally created by @eggsbenedicto on GitHub (Nov 22, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/7794

Hi,

First of all, thanks for your work.

I tried out the llama3.2-vision:90b model on ollama and it seems to underperform the version available on the build.nvidia.com API, with the same prompt and settings. Is this because it is a quantized model? The ollama documentation on the official website says it has "Quantization Q4_K_M"

If so, is it possible to offer an un-quantized or less quantized version in ollama? I usually do AI tasks on a rented h100, so VRAM is not that much of an issue to me.

Thanks

Originally created by @eggsbenedicto on GitHub (Nov 22, 2024). Original GitHub issue: https://github.com/ollama/ollama/issues/7794 Hi, First of all, thanks for your work. I tried out the llama3.2-vision:90b model on ollama and it seems to underperform the version available on the build.nvidia.com API, with the same prompt and settings. Is this because it is a quantized model? The ollama documentation on the official website says it has "Quantization Q4_K_M" If so, is it possible to offer an un-quantized or less quantized version in ollama? I usually do AI tasks on a rented h100, so VRAM is not that much of an issue to me. Thanks
GiteaMirror added the model label 2026-05-04 09:18:43 -05:00
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@rick-github commented on GitHub (Nov 22, 2024):

https://ollama.com/library/llama3.2-vision:90b-instruct-fp16

<!-- gh-comment-id:2493347873 --> @rick-github commented on GitHub (Nov 22, 2024): https://ollama.com/library/llama3.2-vision:90b-instruct-fp16
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@eggsbenedicto commented on GitHub (Nov 22, 2024):

Thanks! Didn't see the drop-down

<!-- gh-comment-id:2493410681 --> @eggsbenedicto commented on GitHub (Nov 22, 2024): Thanks! Didn't see the drop-down
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Reference: github-starred/ollama#67037