To ease the development of CG models and increase their physical relevance and accuracy, we used a benchmark of wide structural diversity to demonstrate that Swarm-CG can be employed with default settings for tuning BP of a variety of CG models of diverse levels of complexity. Swarm-CG systematically yields appropriate sets of BP in the context of the provided model topology and reference AA trajectory, within wall times compatible with molecular modelers' requirements. Using execution mode 1, Rg values of the optimized models were systematically in agreement with the reference AA trajectory. Importantly, Swarm-CG produces sets of BP via an optimization process which objective function is exclusively based on the user-provided AA reference trajectory. Therefore, the BP produced by Swarm-CG are optimized exclusively to reproduce the geometrical behavior observed in the AA trajectory for the molecule of interest. The process of averaging distributions within geoms groups does improve the quality of the reference sampling for large symmetrical molecules and yielded particularly accurate BP in the present benchmark. To this end, the step of defining relevant geoms groups in the preliminary CG model file is crucial. On the other hand, as mentioned before, care must be taken to provide AA reference trajectories that correctly sample the desired geometrical behavior of the molecule in solvent, or other environments.