I’m a bit confused by what you mean here, as cudnn.benchmark shouldn’t ever increase the memory requirements of your model. If there is more memory available, the peak usage can definitely be higher as benchmark will try algorithms that require a larger workspace (temporary global memory). However, this shouldn’t affect the memory requirements as decreasing the available memory will filter out the algorithms that need a larger workspace.