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what are you all running this week on dual 3090
#1
I'm trying to sanity-check my setup.

I'm mostly working with Llama in SGLang on 4090. The part I'm trying to understand is prefill/decode split.

Not looking for the perfect answer, mostly what worked in real use.

This is mostly for local work rather than public serving.
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#2
What worked for me was pretty simple. Before rebuilding anything, I'd test one clean baseline with Gemma and compare from there.
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#3
Quote:What worked for me was pretty simple. Before rebuilding anything, I'd test one clean baseline with Gemma and compare from there.

I'd approach it in a boring order. If you're on TensorRT-LLM, I'd confirm the version first and then reduce variables until the behavior is obvious. Not glamorous advice, but repeatable baselines save a lot of time.

If you post your exact settings, people here can probably narrow it down pretty fast.
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#4
My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at batch size.
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#5
Quote:My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at batch size.

subscribed, curious where this lands.
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#6
that fixed it for me too.
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#7
Did a small comparison this afternoon. I couldn't reproduce the slowdown until I pushed context much higher. The surprise was that memory pressure showed up before throughput collapsed.
learning in public
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#8
that fixed it for me too.
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#9
I hit almost the same issue last night.
retrieval before vibes
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#10
I tested this tonight. I couldn't reproduce the slowdown until I pushed context much higher.
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