The efficient screening of solvents for CO2 capture requires a reliable and robust equation of state to characterize and compare their thermophysical behavior for the desired application. In this work, the potentiality of 14 ionic liquids (ILs) and 7 deep eutectic solvents (DESs) for CO2 capture was examined using soft-SAFT as a modeling tool for the screening of these solvents based on key process indicators, namely, cyclic working capacity, enthalpy of desorption, and CO2 diffusion coefficient. Once the models were assessed versus experimental data, soft-SAFT was used as a predictive tool to calculate the thermophysical properties needed for evaluating their performance. Results demonstrate that under the same operating conditions, ILs have a far superior performance than DESs primarily in terms of amount of CO2 captured, being at least two-folds more than that captured using DESs. The screening tool revealed that among all the examined solvents and conditions, [C4 py][NTf2] is the most promising solvent for physical CO2 capture. The collection of the acquired results confirms the reliability of the soft-SAFT EoS as an attractive and valuable screening tool for CO2 capture and process modeling.