+- Inference (https://www.datasculpting.ai/inference)
+-- Forum: Inference Engines (https://www.datasculpting.ai/inference/forumdisplay.php?fid=9)
+--- Forum: vLLM / SGLang (https://www.datasculpting.ai/inference/forumdisplay.php?fid=36)
+--- Thread: vLLM vs SGLang for small teams (/showthread.php?tid=460)
Pages:
1
2
Re: vLLM vs SGLang for small teams - turboarch95 - 10-03-2026
Maybe, but I had the opposite result. I've seen people blame HBM constraints when the real issue was much more mundane. Not saying you're wrong, just that I wouldn't lock that in as the lesson yet.
Re: vLLM vs SGLang for small teams - batchcraft - 10-03-2026
My first guess would be this: 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.
Re: vLLM vs SGLang for small teams - thetaplane - 10-03-2026
A couple things I'd check first. Before rebuilding anything, I'd test one clean baseline with Mistral and compare from there. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
Re: vLLM vs SGLang for small teams - torchkite - 10-03-2026
Quote:A couple things I'd check first. Before rebuilding anything, I'd test one clean baseline with Mistral and compare from there. A lot of these threads e
My first guess would be this: On 5090, the easiest win is often to back off the aggressive settings and see whether the problem survives. Once you know the plain path works, then add the faster path back in piece by piece.
Re: vLLM vs SGLang for small teams - papermixer4 - 10-03-2026
Tried to reproduce it just now. I couldn't reproduce the slowdown until I pushed context much higher.
Re: vLLM vs SGLang for small teams - batchpeak - 10-03-2026
I hit almost the same issue last night.