Interactive influence diagrams(I-IDs) offer a transparent and representation for the decision-making in multiagent settings. In I-IDs, for the sake of predicting the behavior of other agent accurately, the modeling agent starts from an initial set of possible models for another agent and then maintains belief about which of those models applies. This initial set of models in the model node is typically a fully specification of possible agent types. Although such a rich space gives the modeling agent high accuracy in its beliefs, it will also incur high cost in maintaining those beliefs. In this paper, we demonstrate that we can choose a minimal, but sufficient, space of mental models by combining models that action or utility equivalence. We illustrate our framework using the two-tiger game and provide empirical results by showing the minimal mental model spaces that it generates.