There shouldn't be. Generally speaking, models will be serialized according to their 'native' format for well-known libraries like Tensorflow, xgboost, sklearn, etc. Custom model will be saved with pickle. The files exist on distributed storage as artifacts. MLflow can and does log additional metadata with the model, like its schema, sample input, environment requirements, but these are tiny additional files.
