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NVFP4 / INT4 tradeoffs with PyTorch - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Inference Engines (https://www.datasculpting.ai/inference/forumdisplay.php?fid=9) +--- Forum: Other Engines (https://www.datasculpting.ai/inference/forumdisplay.php?fid=39) +--- Thread: NVFP4 / INT4 tradeoffs with PyTorch (/showthread.php?tid=1078) |
NVFP4 / INT4 tradeoffs with PyTorch - pixelspark - 10-12-2026 Thought I'd post a small recipe because a lot of threads ask similar things. This isn't revolutionary, but the combination of SGLang and A6000 felt surprisingly usable once I tuned around quant drift. Maybe useful as a starting point for newer folks. Re: NVFP4 / INT4 tradeoffs with PyTorch - edgekite - 10-13-2026 What worked for me was pretty simple. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at continuous batching. |