New aerosol modules of global (circulation and chemical transport) models are evaluated. These new modules distinguish among at least five aerosol components: sulfate, organic carbon, black carbon, sea salt, and dust. Monthly and regionally averaged predictions for aerosol mass and aerosol optical depth are compared. Differences among models are significant for all aerosol types. The largest differences were found near expected source regions of biomass burning (carbon) and dust. Assumptions for the permitted water uptake also contribute to optical depth differences (of sulfate, organic carbon, and sea salt) at higher latitudes. The decline of mass or optical depth away from recognized sources reveals strong differences in aerosol transport or removal among models. These differences are also a function of altitude, as transport biases of dust do not always extend to other aerosol types. Ratios of optical depth and mass demonstrate large differences in the mass extinction efficiency, even for hydrophobic aerosol. This suggests that efforts of good mass simulations could be wasted or that conversions are misused to cover for poor mass simulations. In an attempt to provide an absolute measure for model skill, simulated total optical depths (when adding contributions from all five aerosol types) are compared to measurements from ground and space. Comparisons to the Aerosol Robotic Network (AERONET) suggest a source strength underestimate in many models, most frequently for (subtropical) tropical biomass or dust. Comparisons to the combined best of Moderate-Resolution Imaging Spectroradiometer (MODIS) and Total Ozone Mapping Spectrometer (TOMS) indicate that away from sources, model simulations are usually smaller. Particularly large are discrepancies over tropical oceans and oceans of the Southern Hemisphere, raising issues on the treatment of sea salt in models. Totals for mass or optical depth in many models are defined by the absence or dominance of only one aerosol component. With appropriate corrections to that component (e.g., to removal, to source strength, or to seasonality) a much better model performance can be expected. Still, many important modeling issues remain inconclusive as the combined result of poor coordination (different emissions and meteorology), insufficient model output (vertical distributions, water uptake by aerosol type), and unresolved measurement issues (retrieval assumptions and temporal or spatial sampling biases).