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what music do you benchmark to on GB200
#1
Thought I'd post a small recipe because a lot of threads ask similar things.

This isn't revolutionary, but the combination of PyTorch and 5090 felt surprisingly usable once I tuned around workstation thermals.

If someone wants the exact settings I can clean them up and post them.

My use case is pretty ordinary: local chat, some document work, and occasional batch jobs.
context windows are not a product strategy
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#2
Thanks, that helps. I don't think your conclusion is far off. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
context windows are not a product strategy
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#3
A couple questions before I guess too hard. Are you testing this on mini PC or something else?
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#4
That matches what I was seeing. I ended up in about the same place using vLLM. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.
throughput matters, but tail latency matters too
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#5
I'd approach it in a boring order. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at structured output. Not glamorous advice, but repeatable baselines save a lot of time.
routing beats arguing over one perfect model
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#6
Interesting, I hadn't tried that. That matches what I saw on A6000. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
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#7
Quote:Interesting, I hadn't tried that. That matches what I saw on A6000. The biggest change for me was simplifying the stack instead of adding one more opt

That matches what I was seeing. I ended up in about the same place using TensorRT-LLM. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
learning in public
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#8
Interesting, I hadn't tried that. I don't think your conclusion is far off. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
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#9
that fixed it for me too. The logs were somehow calmer than I was.
2x3090 • llama.cpp • too much VRAM is still not enough
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#10
What worked for me was pretty simple. Before rebuilding anything, I'd test one clean baseline with DeepSeek and compare from there. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
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