Metal-free magnetism, as present in systems including molecular magnets, covalent organic frameworks and other organic polymers, has attracted significant research interest in recent years. However, accurately predicting the magnetic interactions in these systems is challenging due to their intrinsic multi-reference nature, meaning that multiple spin-state configurations have small energy splittings. To investigate magnetic interactions, researchers often turn to methods like density matrix renormalization group (DMRG), complete active space self-consistent field (CASSCF) and complete active space configuration interaction (CASCI), which can be enhanced with dynamic electron correlation methods like difference-dedicated configuration interaction (DDCI), complete active space second-order perturbation theory (CASPT2), and n-electron valence second-order perturbation theory (NEVPT2). However, these approaches are computationally demanding and prohibitively expensive for large systems, including periodic structures. Density-functional theory (DFT) offers an alternative way to study the electronic structures of large systems, including periodic ones. Moreover, it provides a starting point for more advanced methods like GW and the random phase approximation (RPA). The quasi-particle description of DFT captures, in principle, static and dynamic correlations. To date, none of the existing functionals provides the quantitative accuracy and reliability to accurately assess the electronic configuration and energy differences in metal-free magnetic systems. A popular solution to improve the description of magnetic behavior in strongly correlated systems with metal centers, where the correlation is dominated by d electrons, is the DFT+U approach, which includes the empirical parameter Hubbard U. However, for metal-free systems, where static electron correlation cannot be associated with a welldefined subset of electrons, the DFT+U approach does not provide a viable solution. Therefore, it is beneficial to have a high-quality dataset with reliable benchmark data to assess the performance of a method for organic systems with non-local spin densities, which will also contribute to the research of two-dimensional polymers or covalentorganic frameworks within a periodic ansatz.