<p>Understanding molecular interactions beyond single-molecule properties is critical for studying real-world chemical systems. Quantum chemical calculations of molecule–molecule interactions are computationally demanding, making large, publicly available datasets scarce. Here, we present an efficient framework for generating initial configurations of molecular interaction systems and construct a molecular interaction dataset, containing 49,620 individual molecules and 247,741 molecular pairs spanning chromophore–solvent, solute–solvent, and drug–drug interactions, each associated with experimentally characterized equilibrium structures. Our dataset can be used for theoretical studies and machine learning applications in chemical sciences, particularly for modeling intermolecular interactions and structure-based prediction of experimental properties. In future work, we plan to expand the dataset to include non-equilibrium structures and atomic forces, thereby broadening its applicability to reaction modeling and force field development. </p>