The smaller vocabulary size allows us to efficiently model larger context, so in addition to the 4-gram LM, we also train a 7-gram LM based on word classes.
to an LM of the same size trained on word identities, the increase in computational resources needed for translation is negligible for the 7-gram word class LM (wcLM).