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Spent some time on this today and wanted to compare notes.
I'm comparing two approaches here: keep it simple on 5090, or squeeze more out of the stack and deal with the complexity.
What would you pick if you had to live with it for a few months?
learning in public
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Good point. The pattern around consumer GPUs has been pretty similar for me. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
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A couple things I'd check first. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at KV cache pressure. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
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I'd approach it in a boring order. On B200, the easiest win is often to back off the aggressive settings and see whether the problem survives. Not glamorous advice, but repeatable baselines save a lot of time.
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My first guess would be this: If you're on LM Studio, I'd confirm the version first and then reduce variables until the behavior is obvious. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
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My first guess would be this: On B200, the easiest win is often to back off the aggressive settings and see whether the problem survives. Once you know the plain path works, then add the faster path back in piece by piece.
2x3090 • llama.cpp • too much VRAM is still not enough