![]() |
|
comparing models without fooling yourself - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Evaluation & Testing (https://www.datasculpting.ai/inference/forumdisplay.php?fid=16) +--- Forum: Benchmarks (https://www.datasculpting.ai/inference/forumdisplay.php?fid=65) +--- Thread: comparing models without fooling yourself (/showthread.php?tid=613) Pages:
1
2
|
comparing models without fooling yourself - sparrowworks88 - 09-30-2026 This keeps coming up in conversation so I figured I'd start a thread. It feels like the conversation has shifted hard toward inference and serving details lately, and honestly that makes sense once you start dealing with quant drift. Wondering if this is just where the whole space is heading now. Re: comparing models without fooling yourself - dockridge - 10-01-2026 Appreciate the detail. I don't think your conclusion is far off. Re: comparing models without fooling yourself - marbletrack - 10-02-2026 A couple things I'd check first. Before rebuilding anything, I'd test one clean baseline with DeepSeek and compare from there. Once you know the plain path works, then add the faster path back in piece by piece. Re: comparing models without fooling yourself - cacheline - 10-02-2026 Tried to reproduce it just now. My result was mixed: first run looked bad, second run looked normal. The main thing that moved was latency, not quality. Re: comparing models without fooling yourself - batchpeak - 10-02-2026 My first guess would be this: If you're on SGLang, 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. Re: comparing models without fooling yourself - benchplease - 10-02-2026 A couple things I'd check first. Before rebuilding anything, I'd test one clean baseline with Mixtral and compare from there. Re: comparing models without fooling yourself - kernelghost - 10-03-2026 I'd approach it in a boring order. If you're on PyTorch, 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. Re: comparing models without fooling yourself - batchfield55 - 10-03-2026 I tested this tonight. My result was mixed: first run looked bad, second run looked normal. The main thing that moved was latency, not quality. Re: comparing models without fooling yourself - cacheline - 10-04-2026 Quote:I tested this tonight. My result was mixed: first run looked bad, second run looked normal. The main thing that moved was latency, not quality. worth checking the driver first. Re: comparing models without fooling yourself - batchpeak - 10-04-2026 What worked for me was pretty simple. On GB200, 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. |