Those two metrics will converge as the size of the text being compressed goes to infinity. It's necessary to include model size for things like the Hutter prize that involve compressing a fixed text (to avoid hard-coding) but isn't usually a useful metric for compression, especially because it will cause the compression ratio to depend on the size of the data being compressed.

Edit: I thought the model in the above paper was pre-trained, but apparently it's only trained on the data as it arrives! That's indeed a very interesting approach, I wouldn't have expected that neural network models would converge quickly enough for it to be useful.