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Search / Retrieval / Reranking discussion on B200 - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: RAG & Knowledge Systems (https://www.datasculpting.ai/inference/forumdisplay.php?fid=14) +--- Forum: Search / Retrieval / Reranking (https://www.datasculpting.ai/inference/forumdisplay.php?fid=61) +--- Thread: Search / Retrieval / Reranking discussion on B200 (/showthread.php?tid=596) |
Search / Retrieval / Reranking discussion on B200 - cudaworks - 09-29-2026 Did a bit of testing and thought I'd post the result here. Short version: TensorRT-LLM behaved well for me, but only after I stopped ignoring prefix caching. Curious if anyone else landed in the same place. I care more about stability than squeezing the last possible tokens/sec out of it. Re: Search / Retrieval / Reranking discussion on B200 - signalpeak - 09-30-2026 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: Search / Retrieval / Reranking discussion on B200 - visionyard23 - 09-30-2026 Thanks, that helps. I ended up in about the same place using vLLM. The biggest change for me was simplifying the stack instead of adding one more optimization layer. |