Inference
power delivery for 24/7 serving - Printable Version

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power delivery for 24/7 serving - edgequill - 08-29-2026

Thought I'd post a small recipe because a lot of threads ask similar things.

Just sharing a setup that ended up working reasonably well: Gemma, TensorRT-LLM, A6000, with a lot of attention on tool calling.

Maybe useful as a starting point for newer folks.


Re: power delivery for 24/7 serving - phasenode - 08-31-2026

I'd start with the simpler stack.


Re: power delivery for 24/7 serving - latentpeak22 - 08-31-2026

same here on my side.


Re: power delivery for 24/7 serving - plainscope50 - 09-03-2026

Appreciate the detail. 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.

I'm happy to test one more variant if you want a second data point.


Re: power delivery for 24/7 serving - vectorcrate98 - 09-03-2026

I'd start with the simpler stack.


Re: power delivery for 24/7 serving - batchwire - 09-03-2026

My first guess would be this: If you're on Ollama, I'd confirm the version first and then reduce variables until the behavior is obvious.


Re: power delivery for 24/7 serving - sanevault - 09-04-2026

I'd approach it in a boring order. On Threadripper box, 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.


Re: power delivery for 24/7 serving - tensorport - 09-04-2026

Ran a quick check on my box. I couldn't reproduce the slowdown until I pushed context much higher.


Re: power delivery for 24/7 serving - routecraft - 09-04-2026

Need a little more detail here. Is this local-only or are you routing anything externally?


Re: power delivery for 24/7 serving - batchwire - 09-05-2026

My first guess would be this: If you're on LM Studio, I'd confirm the version first and then reduce variables until the behavior is obvious.