I agree with your opinion about cuda context will consume some GPU memory. I think that’s why nvidia-smi result different with torch.cuda.max_memory_reserved() result. But that answer can’t explain why mobilenetV3_maskrcnn use more GPU memory on peak but they can be deploy three model currently into single GPU, but resnet50_maskrcnn could do this two. Or there is something wrong in my understanding?