The National Aeronautics and Space Administration (NASA) Goddard Earth Observing System global circulation model (GCM) is evaluated through a cascade of simulations with increasing horizontal resolution. This model employs a nonhydrostatic dynamical core and includes a scale?aware, deep convection parameterization (DPCP). The 40?day simulations at six resolutions (100 km to 3 km) with unvarying model formulation were produced. At the highest resolution, extreme experiments were carried out: one with no DPCP and one with its scale awareness eliminated. Simulated precipitation, radiative balance, and atmospheric thermodynamic and dynamical variables are well reproduced with respect to both observational and reanalysis data. As model resolution increases, the convective precipitation smoothly transitions from being mostly produced by the convection parameterization to the cloud microphysics parameterization. However, contrary to current thought, these extreme cases argue for maintaining, to some extent, the scale?aware DPCP even at 3?km scale, as the run relying solely on explicit grid?scale production of rainfall performs more poorly at this resolution. Plain Language Summary Global circulation models (GCMs) are the means we have to predict the weather and assess the future climate on daily, seasonal, and even century?long timescales. GCMs are computational tools that employ approximate forms of the fundamental equations governing the time evolution of the atmosphere. Given the broad spectrum of scales of the atmospheric phenomenon, computational limitations require parameterizations for processes not explicitly resolved at the model computational grid. The next generation of the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System (GEOS) GCM is being developed as a unified, seamless model to be applied across a broad spectrum of spatial and temporal scales of the atmospheric motions. This paper provides an evaluation of relevant aspects of the GEOS forecasts across a pertinent range of horizontal resolution with an unvarying model formulation. We focus specifically on the parameterization of deep convection and evaluate its influence on model results down to the a few kilometers scale. We arrive at the unexpected conclusion that a kilometer?scale resolution where convection is mostly explicitly resolved perform worse.