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serving on Blackwell - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Inference Engines (https://www.datasculpting.ai/inference/forumdisplay.php?fid=9) +--- Forum: TensorRT-LLM (https://www.datasculpting.ai/inference/forumdisplay.php?fid=37) +--- Thread: serving on Blackwell (/showthread.php?tid=1169) |
serving on Blackwell - kernelgrid - 10-14-2026 Did a bit of testing and thought I'd post the result here. I tried this with Kimi using SGLang on Threadripper box. The headline result was better than I expected, but embeddings still ended up being the limiting factor. Curious if anyone else landed in the same place. For context, I'm not chasing leaderboard numbers. I mostly want the system to feel consistent day to day. Re: serving on Blackwell - macrotinker - 10-15-2026 I don't think that's the whole story. I've seen people blame NVFP4 when the real issue was much more mundane. Worth testing the simpler explanation before adopting the more interesting one. Re: serving on Blackwell - rocmriley - 10-15-2026 Interesting, I hadn't tried that. That matches what I saw on Threadripper box. The biggest change for me was simplifying the stack instead of adding one more optimization layer. |