This paper presents an equilibrium modeling scheme for describing network flows formed by behaviorally inertial travelers routing in stochastic networks with a finite number of states. The network flow pattern is an aggregation result of recurrent traffic dynamics caused by varying network states. A finite-dimensional variational inequality model is formulated to describe the cross-state equilibrium conditions among heterogeneous travelers with different inertial degrees and knowledge structures. This model allows for traveler's partial understanding and inertial effect in perceiving varying network conditions and provides a different perspective (from existing stochastic and Markovian network equilibrium approaches) to describe traffic flow variations across multiple network scenarios. Numerical results from a few stochastic network examples demonstrate the validity and effectiveness of our methodology in modeling the inertia phenomenon in route choice behavior and the efficacy of using traveler information systems to eliminate the inertia effect.