Are more classes more favorable than a single combined class?
So what you are interested in (in terms of prediction) is $n+1$ classes, where the last class is $m=1$. This would be my default model. In other words, I don‘t see why you should have $m$ additional outcomes if these outcomes are irrelevant for your task. 

For the quality of a prediction, features $X$ matter the most. I‘m not aware that the classes are relevant unlike your outcome (=classes) have an order. 

However, ultimately you need to test which model performs best. So by the parsimony principle, start with a simple model and gradually see if adding complexity delivers a better result (by a predefined measure such as accuracy).