The GPU might be utilized completely (regarding the compute), while the memory isn’t fully used (similar to your PC, where the CPU might be fully utilized, while your RAM is quite empty).
Usually PyTorch kernels are implemented in such a way to try to fully use the GPU, so that running multiple models in parallel might not be possible (you would also have to use CUDA streams for it, which might be tricky).