It should increase quality since those layers can specialize on subsets of the training data. This means that getting better in one domain won't make the model

It should increase quality since those layers can specialize on subsets of the training data. This means that getting better in one domain won't make the model worse in all the others anymore. We can't really tell what the router does. There have been experiments where the router in the early blocks was compromised, and quality only suffered moderately. In later layers, as the embeddings pick up more semantic information, it matters more and might approach our naive understanding of the term "expert".