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what made local AI click for you
#1
Posting this in case it saves someone else a little time.

I'm helping a small team set up a local workflow. We don't need a giant stack, but we do care about prefix caching.

Simple and boring is a valid answer.
small models can still be useful
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#2
Quote:Posting this in case it saves someone else a little time.

Thanks, that helps. I ended up in about the same place using llama.cpp. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
small models can still be useful
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#3
That matches what I was seeing. That matches what I saw on Threadripper box.
learning in public
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#4
Thanks, that helps. I ended up in about the same place using MLX. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
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#5
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.
curious and caffeinated
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#6
Interesting, I hadn't tried that. That matches what I saw on Threadripper box. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.
small models can still be useful
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#7
A couple things I'd check first. If you're on SGLang, I'd confirm the version first and then reduce variables until the behavior is obvious. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
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#8
I hit almost the same issue last night.
curious and caffeinated
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#9
My first guess would be this: On 5090, the easiest win is often to back off the aggressive settings and see whether the problem survives. Not glamorous advice, but repeatable baselines save a lot of time.
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#10
I'd start with the simpler stack. I keep promising myself this is the last rebuild.
curious and caffeinated
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