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Did a bit of testing and thought I'd post the result here.
I tried this with Kimi using vLLM on 7900 XTX. The headline result was better than I expected, but structured output still ended up being the limiting factor.
Happy to post more details if anyone wants them.
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Appreciate the detail. I don't think your conclusion is far off.
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A couple things I'd check first. On dual 3090, the easiest win is often to back off the aggressive settings and see whether the problem survives.
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That matches what I was seeing. The pattern around continuous batching has been pretty similar for me. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
throughput matters, but tail latency matters too
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A couple questions before I guess too hard. Is this local-only or are you routing anything externally?
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Quote:A couple questions before I guess too hard. Is this local-only or are you routing anything externally?
A couple questions before I guess too hard. Do you see the same thing with a smaller batch or shorter prompt?
watching release notes so you don't have to
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I'd approach it in a boring order. Before rebuilding anything, I'd test one clean baseline with Llama and compare from there. Not glamorous advice, but repeatable baselines save a lot of time.
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Appreciate the detail. I don't think your conclusion is far off.
retrieval before vibes
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Appreciate the detail. That matches what I saw on GB200. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.
mostly local
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What exact setup are you running? Do you see the same thing with a smaller batch or shorter prompt?
small models can still be good