![]() |
|
benchmarks that map to real use with vLLM - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Evaluation & Testing (https://www.datasculpting.ai/inference/forumdisplay.php?fid=16) +--- Forum: Evals (https://www.datasculpting.ai/inference/forumdisplay.php?fid=66) +--- Thread: benchmarks that map to real use with vLLM (/showthread.php?tid=126) Pages:
1
2
|
Re: benchmarks that map to real use with vLLM - thetanest - 09-06-2026 What worked for me was pretty simple. Before rebuilding anything, I'd test one clean baseline with Mixtral and compare from there. Re: benchmarks that map to real use with vLLM - batchsize - 09-09-2026 A couple things I'd check first. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at speculative decoding. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. Re: benchmarks that map to real use with vLLM - quantghost - 09-10-2026 Interesting, I hadn't tried that. I don't think your conclusion is far off. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing. There are a few different conversations hiding inside this thread, so being explicit about the goal helps. Re: benchmarks that map to real use with vLLM - northcraft90 - 09-10-2026 Tried to reproduce it just now. On Threadripper box with PyTorch, I saw basically the same behavior. The main thing that moved was latency, not quality. Re: benchmarks that map to real use with vLLM - ggufwire22 - 09-10-2026 Quote:Tried to reproduce it just now. On Threadripper box with PyTorch, I saw basically the same behavior. The main thing that moved was latency, not qualit following this because I'm in the same boat. Re: benchmarks that map to real use with vLLM - sanevault - 09-10-2026 Maybe, but I had the opposite result. I get why that seems right, but on 4090 the bottleneck felt elsewhere. Worth testing the simpler explanation before adopting the more interesting one. |