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Posting this in case it saves someone else a little time.
I'm not trying to build a perfect architecture diagram. I just want a sane starting point around PyTorch and 5090.
Simple and boring is a valid answer.
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I'd approach it in a boring order. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at token cost. Not glamorous advice, but repeatable baselines save a lot of time.
measure twice, benchmark three times
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My first guess would be this: On mini PC, the easiest win is often to back off the aggressive settings and see whether the problem survives.
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My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at HBM constraints. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. Turns out 'just one more test' was a lie.
measure twice, benchmark three times
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Appreciate the detail. 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.
measure twice, benchmark three times
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I think the bottleneck is somewhere else. I get why that seems right, but on 5090 the bottleneck felt elsewhere. Worth testing the simpler explanation before adopting the more interesting one.
measure twice, benchmark three times
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Thanks, that helps. I ended up in about the same place using vLLM.
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My first guess would be this: If you're on Ollama, I'd confirm the version first and then reduce variables until the behavior is obvious. Not glamorous advice, but repeatable baselines save a lot of time.
measure twice, benchmark three times
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Interesting, I hadn't tried that. I ended up in about the same place using MLX. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
measure twice, benchmark three times
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My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at consumer GPUs. Once you know the plain path works, then add the faster path back in piece by piece.
measure twice, benchmark three times