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Thought I'd post a small recipe because a lot of threads ask similar things.
Just sharing a setup that ended up working reasonably well: Kimi, vLLM, 7900 XTX, with a lot of attention on batch size.
Maybe useful as a starting point for newer folks. Turns out 'just one more test' was a lie.
learning in public
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A couple questions before I guess too hard. Are you testing this on mini PC or something else?
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Tried to reproduce it just now. My result was mixed: first run looked bad, second run looked normal. I expected the model choice to matter more than it did.
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worth checking the driver first.
routing beats arguing over one perfect model
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Tried to reproduce it just now. My result was mixed: first run looked bad, second run looked normal. The surprise was that memory pressure showed up before throughput collapsed.
2x3090 • llama.cpp • too much VRAM is still not enough
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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 router policy. Once you know the plain path works, then add the faster path back in piece by piece.
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Ran a quick check on my box. On Threadripper box with PyTorch, I saw basically the same behavior. The main thing that moved was latency, not quality.
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Thanks, that helps. That matches what I saw on M3 Max.
learning in public
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Appreciate the detail. That matches what I saw on dual 3090. The biggest change for me was simplifying the stack instead of adding one more optimization layer.