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serving on Blackwell for Phi - 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 for Phi (/showthread.php?tid=1285) Pages:
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serving on Blackwell for Phi - pixelcrate82 - 10-16-2026 I figured I'd ask here before changing everything. I'm mostly working with Phi in TensorRT-LLM on Threadripper box. The part I'm trying to understand is quant drift. Would appreciate practical advice rather than theory. For context, I'm not chasing leaderboard numbers. I mostly want the system to feel consistent day to day. Re: serving on Blackwell for Phi - macrotinker - 10-16-2026 What worked for me was pretty simple. If you're on Ollama, I'd confirm the version first and then reduce variables until the behavior is obvious. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. There are a few different conversations hiding inside this thread, so being explicit about the goal helps. Re: serving on Blackwell for Phi - sysstation69 - 10-16-2026 What worked for me was pretty simple. Before rebuilding anything, I'd test one clean baseline with Qwen and compare from there. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it. Re: serving on Blackwell for Phi - northcraft90 - 10-16-2026 Need a little more detail here. Is this local-only or are you routing anything externally? Re: serving on Blackwell for Phi - kernelpeak - 10-18-2026 Quote:Need a little more detail here. Is this local-only or are you routing anything externally? I don't think that's the whole story. The reported numbers can look compelling, but in ordinary usage I didn't see the same benefit. Re: serving on Blackwell for Phi - torchtrack24 - 10-18-2026 Tried to reproduce it just now. I couldn't reproduce the slowdown until I pushed context much higher. Re: serving on Blackwell for Phi - kernelgrid - 10-18-2026 Thanks, that helps. I don't think your conclusion is far off. The biggest change for me was simplifying the stack instead of adding one more optimization layer. Re: serving on Blackwell for Phi - torchtrack24 - 10-18-2026 What worked for me was pretty simple. If you're on TensorRT-LLM, I'd confirm the version first and then reduce variables until the behavior is obvious. Re: serving on Blackwell for Phi - routecrate - 10-18-2026 Did a small comparison this afternoon. My result was mixed: first run looked bad, second run looked normal. Re: serving on Blackwell for Phi - rocmmixer - 10-18-2026 I tested this tonight. My result was mixed: first run looked bad, second run looked normal. The main thing that moved was latency, not quality. |