Also, Tensorflow’s default setting is allocating full GPU memory during the run. Hence, with Keras and TF as backend, you’re most likely to see ~100% memory being allocated. This default behavior can be changed by @jeremy’s tip here (Tip: Clear tensorflow GPU memory).
PyTorch is nicer on this aspect. Allocating just enough memory as it needs.
Edit: @anandsaha just beat me to my comment !