Unverified50% confidenceFactExact time
On GPUs, 19 of the 50 configurations showed actual peak memory deviating from the predicted value, and the numerical results also changed.
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10/19/2026
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UnverifiedTraditional LLM inference frameworks pre-allocate contiguous GPU memory for each request, leading to memory fragmentation, with actual GPU utilization often falling below 50%.71% similarUnverifiedThe GPU resources required for a single inference of a hundred-billion-parameter flagship model may be 10 to 20 times higher than those of a ten-billion-parameter model.69% similarUnverifiedWithout a sufficiently optimized software stack, actual GPU utilization often reaches only 30–50% of the theoretical peak.68% similarUnverifiedThe developer cautions that the sample size of 18 matchups is insufficient to rank the models reliably.67% similarUnverifiedExperimental results show that under model misspecification conditions, PrO-GPs produce better calibrated predictive distributions than standard GP methods.67% similar
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