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Good point. I don't think your conclusion is far off. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.
2x3090 • llama.cpp • too much VRAM is still not enough
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Can you fill in a bit more context? Is this local-only or are you routing anything externally?
2x3090 • llama.cpp • too much VRAM is still not enough
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Did a small comparison this afternoon. On Threadripper box with TensorRT-LLM, I saw basically the same behavior. The main thing that moved was latency, not quality.
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What exact setup are you running? What model, what runtime, and roughly what context size?
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What exact setup are you running? Do you see the same thing with a smaller batch or shorter prompt?
2x3090 • llama.cpp • too much VRAM is still not enough