Furthermore, within the realm of GNN based models, CGCNN and GATGNN exhibit notably lower time consumption (less than 0.07 s per data point) than ALIGNN and Matformer (higher than 0.17 s per data point) as depicted in Figure , while the prediction accuracy of the former two models is slightly inferior to that of the latter two, indicated by the lower R 2 and higher MAE values (see Table and). The ALIGNN model integrates additional bond angular information as input , while the Matformer model encode a complex transformer architecture , which may result in lower computational efficiency compared to CGCNN and GATGNN.