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framework overhead in real deployments - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Drivers / Frameworks / Toolkits (https://www.datasculpting.ai/inference/forumdisplay.php?fid=8) +--- Forum: PyTorch / JAX / Other Frameworks (https://www.datasculpting.ai/inference/forumdisplay.php?fid=34) +--- Thread: framework overhead in real deployments (/showthread.php?tid=1243) Pages:
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Re: framework overhead in real deployments - kernelghost - 10-19-2026 Not sure I agree there. I wouldn't optimize around that first. On my side the bigger swing came from the runtime and not the model. Not saying you're wrong, just that I wouldn't lock that in as the lesson yet. Re: framework overhead in real deployments - fusedhall - 10-19-2026 following this because I'm in the same boat. Re: framework overhead in real deployments - llmarch83 - 10-19-2026 Thanks, that helps. That matches what I saw on 5090. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable. Re: framework overhead in real deployments - sanescope - 10-19-2026 Quote:following this because I'm in the same boat. I'd approach it in a boring order. Before rebuilding anything, I'd test one clean baseline with Qwen and compare from there. Once you know the plain path works, then add the faster path back in piece by piece. |