Solved by eqy in post #2 
              
              
                Great question. There are several things going on here. First, a bare CUDA context on a GPU will use about 300MiB VRAM (this gets initialized the first time you call .cuda()). Then libtorch_cuda.so (containing all GPU kernels for various tensor operators, etc.) will be loaded into VRAM taking anothe…