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embedding model you trust
#1
Did a bit of testing and thought I'd post the result here.

I tried this with Phi using SGLang on M3 Max. The headline result was better than I expected, but structured output still ended up being the limiting factor.

Nothing scientific here, just practical notes from a real setup.

My use case is pretty ordinary: local chat, some document work, and occasional batch jobs.
small models can still be good
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#2
Maybe, but I had the opposite result. I wouldn't optimize around that first. On my side the bigger swing came from the runtime and not the model.
trying not to rebuild again
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#3
A couple things I'd check first. Before rebuilding anything, I'd test one clean baseline with Kimi and compare from there. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
Mostly CUDA, sometimes wrong, usually measured
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#4
Ran a quick check on my box. 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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#5
Quote:Ran a quick check on my box. My result was mixed: first run looked bad, second run looked normal. I expected the model choice to matter more than it d

That matches what I was seeing. That matches what I saw on M3 Max. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing. I keep promising myself this is the last rebuild.
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#6
Maybe, but I had the opposite result. I've seen people blame tail latency when the real issue was much more mundane. Worth testing the simpler explanation before adopting the more interesting one.
still benchmarking everything
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