Confidential GPU inference under model swapping is significantly slower than non-confidential, and the gap is driven by model loading, not by inference compute.
The case for confidential com- puting: Delivering business value through protected, confidential data processing,
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Performance of Confidential Computing GPUs
Confidential GPU inference under model swapping is significantly slower than non-confidential, and the gap is driven by model loading, not by inference compute.