abstract: Proteins, individual cells, and cell populations denote dierent levels of an organizational hierarchy, each of which with its own dynamics. Multi-level modeling is concerned with describing a system at these dierent levels and relating their dynamics. Referring to space, multi-level modeling typically implies compartmental dynamics. We will present three dierent rule-based modeling approaches that support dynamic nesting and integrate compartmental dynamics with a) non-spatial stochastic simulation (Gillespie-type), b) grid-based stochastic reaction diusion simulation (Next Subvolume Method) and particle-based simulation in continuous space (pure Brownian Dynamics), and c) particle-based simulation that in addition uses potentials for particle-particle interactions. We will discuss how the dierent approaches aim at bridging molecular and cellular scales from the modeling point of view (and the role that the expressiveness of the modeling languages play in this), discuss implications for simulation, and illuminate features of the approaches and lessons learned based on a set of small cell biological models.