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do you even need a vector DB here
#1
Did a bit of testing and thought I'd post the result here.

Short version: vLLM behaved well for me, but only after I stopped ignoring embeddings.

Nothing scientific here, just practical notes from a real setup.
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#2
Tried to reproduce it just now. On dual 3090 with llama.cpp, I saw basically the same behavior.
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#3
I'd start with the simpler stack.
measure twice, benchmark three times
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#4
Can you fill in a bit more context? What model, what runtime, and roughly what context size?

There are a few different conversations hiding inside this thread, so being explicit about the goal helps.
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#5
What exact setup are you running? Is this local-only or are you routing anything externally?
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#6
I'd approach it in a boring order. Before rebuilding anything, I'd test one clean baseline with Gemma and compare from there.
mostly local
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#7
I'd approach it in a boring order. On B200, 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.
image models by night, local pipelines by day
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#8
Quote:I'd approach it in a boring order. On B200, the easiest win is often to back off the aggressive settings and see whether the problem survives. Not gla

A couple questions before I guess too hard. Is this local-only or are you routing anything externally?
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#9
What worked for me was pretty simple. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at batch size.
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#10
Quote:What worked for me was pretty simple. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at batch size.

Not sure I agree there. I've seen people blame prefix caching when the real issue was much more mundane.
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