+- 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=1119)
Pages:
1
2
Re: vLLM vs SGLang for small teams - southpatch - 10-18-2026
Did a small comparison this afternoon. The issue went away once I changed one setting and restarted the stack cleanly. I expected the model choice to matter more than it did. At this point the real bottleneck is my patience.
Re: vLLM vs SGLang for small teams - promptpoint - 10-18-2026
Maybe, but I had the opposite result. I get why that seems right, but on 5090 the bottleneck felt elsewhere. Worth testing the simpler explanation before adopting the more interesting one.
Re: vLLM vs SGLang for small teams - thetaplane - 10-18-2026
Maybe, but I had the opposite result. I get why that seems right, but on A6000 the bottleneck felt elsewhere. Not saying you're wrong, just that I wouldn't lock that in as the lesson yet.
Re: vLLM vs SGLang for small teams - promptpoint - 10-19-2026
Thanks, that helps. The pattern around MoE serving has been pretty similar for me. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.