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This keeps coming up in conversation so I figured I'd start a thread.
One thing I keep noticing is that people underestimate workstation thermals until they actually try to run this stuff for more than one afternoon.
Curious whether that lines up with what other people are seeing.
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Did a small comparison this afternoon. The issue went away once I changed one setting and restarted the stack cleanly. The surprise was that memory pressure showed up before throughput collapsed.
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That matches what I was seeing. I don't think your conclusion is far off. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
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I don't think that's the whole story. The reported numbers can look compelling, but in ordinary usage I didn't see the same benefit.
still benchmarking everything
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Thanks, that helps. The pattern around KV cache pressure 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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That matches what I was seeing. I don't think your conclusion is far off. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
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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Can you fill in a bit more context? Is this local-only or are you routing anything externally?
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A couple questions before I guess too hard. What model, what runtime, and roughly what context size?