Impact of distribution strategy on keras SavedModel variables size on disk

When I save a tf.keras model compiled with a MirroredStrategy on a Vertex AI workbench instance with 4 T4 GPUs attached, the resulting SavedModel variables are 3x the size on disk (1.3GB) of a model compiled on the same instance with the default strategy and then saved (430MB).

If I reload the 1.3GB saved model with the default strategy, then resave it, the variables remain at 1.3GB, instead of shrinking to 430MB.

I don’t even have to train the compiled model to see these differences.

I’ve read the guides and tutorials about model saving and loading, and I’m still struggling to understand why this happens. Can anyone shed some light? Is this known behavior?