The Indian Ocean Dipole (IOD) can significantly influence wind speed (WS) patterns in the Tropical Indian Ocean (TIO). However, the capability of climate models to replicate the impact of IOD on WS still remains inadequately quantified. This study evaluated the performance of 24 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating WS responses to IOD over the Indian Ocean, based on historical simulations spanning the period 1958–2014 during the JJA and SON seasons. The evaluation employed four skill metrics—interannual variability score (IVS), M-Score, root mean square error (RMSE), and Taylor skill score (TSS) in order to assess the model accuracy. A Comprehensive Rating Index (CRI) was used to rank the model performance across different regions and seasons in the study domain. Results indicate that IOD plays a pivotal role in modulating WS in the Bay of Bengal (BOB), Arabian Sea (AS), and Northern Indian Ocean (NIO), with CMIP6 models exhibiting varying skill levels in simulating these responses. AS exhibited the highest variability and uncertainty during JJA, characterized based on larger RMSE and IVS values and lower M-Score, while the NIO showed superior performance with minimal variability and higher consistency. During SON, the model performance improved across all regions, though NIO remains the most consistent. Study indicates that top-performing models for JJA are MIROC6 (AS), MME (BOB), and CESM2 (NIO), while for SON, TaiESM1 (AS), MIROC6 (BOB), and CESM2-WACCM (NIO) ranked the highest. Overall, the models MIROC6, CESM2, and CESM2-WACCM demonstrated consistently higher performance across different regions and seasons, highlighting the robustness in capturing WS responses to IOD. Additionally, the CMIP6 models exhibit significant uncertainty over the AS during JJA in the Indian Ocean.