Observations show that soil microorganisms can survive periods of aridity and recover rapidly after wetting events. This behavior can be explained by a moisture-dependent adaptation (i.e. the ability to transition between a dormant state in dry conditions and an active state in wet conditions). Though this dynamic behavior has been previously incorporated into modeling frameworks, a direct comparison between a model application of this active-dormant transition mechanism and a more simplified first-order model has yet to be made. Here, we developed two models, one using simplified first-order kinetics and the other featuring a process-based rate expression incorporating the transition between active and dormant biomass. The two approaches are contrasted through a benchmarking exercise using a set of time series soil incubation datasets. We evaluated the two models using an Akaike Information Criterion (AIC). Combining the AIC evaluation and model-data comparison, we conclude that the dormancy-incorporated model performs better for shallow soils (above 108 cm), despite the added parameters required. In addition, this model is uniquely capable of reproducing transient CO₂ flux rates associated with dynamic microbial response to changing soil moisture. In contrast, the first-order model achieves better AIC scores when simulating the incubation data obtained from our deepest soils (112–165 cm). However, deep soils constitute a minor contribution to the overall CO₂ flux of an intact soil column. Thus, the dormancy-incorporated model may better simulate respiration of the whole soil.