To compare the performance of Swarm-CG for bonded parametrization with respect to manually parametrized CG models, we first collected several MARTINI models available from the literature and from previous results of our group. We selected the following molecular dataset based on CG data availability and structural diversity: 1,3,5-benzenetricarboxamides (BTA) and benzotrithiophene (BTT) decorated by L-phenylalanine (BTT-F) and octaethylene glycol side-chains, naphthalene diimide (NDI), Zn-porphyrin based molecule, β-Cyclodextrin and poly(amidoamine) dendrimers of generation 1 and 2 (PAMAM G1 and G2). Their CG topologies, selected bead types and non-bonded interactions force field were used as provided, except for β-Cyclodextrin and PAMAM G1 and G2 for which CG topologies were built by truncating the existing CG models of β-Cyclodextrin dimer and PAMAM G5 models. Additionally, two last molecules expand the benchmark and improve its structural diversity: a pillar[5]arene and sperminefunctionalized branched dendron. For the spermine dendron and pillar [5]arene, we built CG models from scratch in the framework of MARTINI using the CG bead types presented in Figure . For the pillar [5]arene and the dendron there are no previously developed manually-optimized CG models to compare with, and the performance of Swarm-CG has been evaluated exclusively with respect to data from the AA-mapped trajectories in these cases. For these 9 molecules, we created AA models and generated trajectories for each single molecule in solvent using time steps of 2 fs and extensive sampling (Table and SI section 2.1), which are used as a trusted reference for bonded parametrization of CG models and benchmarking of Swarm-CG. Where present, non-bonded interactions were further tuned as described in associated literature, starting from the cited force field.