Objective: This study aimed to compare the accuracy of six new generation intraocular lenses (IOL) refractive power calculation formulas (Barrett Universal Ⅱ [BU Ⅱ ], Emmetropia Verifying Optical [EVO], Hill-Radial Basis Function [Hill-RBF], Kane, Ladas Super Formula [LSF], T2) and traditional formulas (Haigis, Hoffer Q, Holladay 1, SRK/ T). Methods: The patients who received cataract surgery in the Eye Hospital of Wenzhou Medical University from January 2022 to June 2022 were included in this study. Age, gender, axial length (AL), mean keratometry, anterior chamber depth, IOL constant and power, and postoperative refraction results were collected. The prediction accuracy of these ten IOL power calculation formulas was analyzed, including mean prediction error (ME) and its standard deviation, mean absolute prediction error (MAE), median absolute prediction error (MedAE), maximum absolute prediction error (MaxAE), the percentage of eyes of PE within the range of ±0.25 D, ±0.5 D, ±0.75 D, ±1.0 D (%±0.25 D,%±0.50 D, %±0.75 D, %±1.00 D). Results: 506 eyes of 506 patients were included. Kane has the lowest MAE (0.411).%±0.25 D of Hill-RBF was the highest (40.91%), %±0.50 D or %±0.75 D of EVO was the highest (69.37%, 86.17%), and %±1.00 D of BU Ⅱ and Hill-RBF was the highest (94.07%). There are significant differences in MAE, %±0.50 D, %±0.75 D, and %±1.00 D among all formulas (P<0.05). Still, pairwise comparison only found differences between EVO (86.17%), Hill-RBF (85.97%), Kane (85.57%), and Hoffer Q (81.42%) in %±0.75 D (all P<0.05). In AL subgroup, the MAE of EVO (0.390), Hill-RBF (0.388), T2 (0.423) and Kane (0.393) in long AL group was different from that of Hoffer Q (0.681) and Holladay 1 (0.654) (all P<0.05), the difference of %±0.50D of EVO (74.47%) compared with Hoffer Q (46.81%) (P=0.017). Conclusion: The new generation of IOL power calculation formulas have good accuracy in IOL power prediction, but for eyes with different axial lengths and keratometry, it is necessary to optimize the selection of formulas to improve the prediction accuracy further.