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Thanks, that helps. That matches what I saw on B200. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
There are a few different conversations hiding inside this thread, so being explicit about the goal helps.
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Thanks, that helps. I ended up in about the same place using PyTorch. 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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Interesting, I hadn't tried that. The pattern around prefix caching has been pretty similar for me. The biggest change for me was simplifying the stack instead of adding one more optimization layer.