Understanding the thermomechanical and conformational properties of semiconducting donor−acceptor conjugated polymers (D-A CPs) at a fundamental molecular scale is essential for the design of high-performance devices. However, the substantial computational demands of all-atom (AA) simulations and the complex heterogeneous structures of CPs pose significant challenges in thoroughly investigating the properties of CPs approaching the real devices scale. Herein, leveraging the wellestablished framework of the energy renormalization (ER) approach, we develop a temperature-and architecture-transferable chemistry-specific coarse-grained (CG) model for poly-(diketopyrrolopyrrole-co-thiophene) (PDPPT)-based D-A CPs with significantly improved computational efficiency. Our results show excellent agreement between AA and CG simulations in predicting key properties such as density, Debye−Waller factor, and Young's modulus across a wide range of temperature and chain architectures. Specifically, the ER-corrected CG model captures trends in glass transition temperature (T g ) and mechanical properties, aligning closely with experimental data. The CG model reveals that longer side chain lengths and less bulky backbone conjugation units induce a lower T g and Young's modulus, with bulky backbone units exhibiting slower dynamics. The localization model accurately predicts relaxation times across different molecular architectures. Additionally, the CG model's conformational properties align with experimental data and theoretical worm-like chain models, showing that persistence length increases with longer side chains, while bulky backbone moieties decrease it. These findings deepen our understanding of the complex interactions between flexible side chains and rigid backbones in CPs with diverse architectures, offering important insights for the strategic design of CPs with tailored properties.