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recipes for a good local stack - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: LLM Models (https://www.datasculpting.ai/inference/forumdisplay.php?fid=12) +--- Forum: Open Weight (https://www.datasculpting.ai/inference/forumdisplay.php?fid=49) +---- Forum: Local (https://www.datasculpting.ai/inference/forumdisplay.php?fid=51) +---- Thread: recipes for a good local stack (/showthread.php?tid=977) Pages:
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Re: recipes for a good local stack - quietcraft - 10-14-2026 Ran a quick check on my box. I couldn't reproduce the slowdown until I pushed context much higher. I expected the model choice to matter more than it did. Re: recipes for a good local stack - mintstation99 - 10-14-2026 What worked for me was pretty simple. If you're on LM Studio, I'd confirm the version first and then reduce variables until the behavior is obvious. Once you know the plain path works, then add the faster path back in piece by piece. Re: recipes for a good local stack - rocmhouse90 - 10-15-2026 My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at long context. Not glamorous advice, but repeatable baselines save a lot of time. Re: recipes for a good local stack - kernelgrid - 10-18-2026 A couple things I'd check first. On Threadripper box, the easiest win is often to back off the aggressive settings and see whether the problem survives. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. Re: recipes for a good local stack - rocmriley - 10-19-2026 Quote:A couple things I'd check first. On Threadripper box, the easiest win is often to back off the aggressive settings and see whether the problem survive Did a small comparison this afternoon. On 5090 with TensorRT-LLM, I saw basically the same behavior. The main thing that moved was latency, not quality. |