Abstract Indian Space Research Organization (ISRO) recently launched the meteorological satellite Microsat‐2B (M2B), which provides high‐resolution atmospheric moisture radiance observations, crucial for improving the predictability of numerical weather prediction (NWP) models. This study evaluates the impact of assimilating M2B radiances into the NCMRWF Global Forecast System (NGFS‐T1534) using the GSI‐3DVar assimilation system. Spectral and transmittance coefficients, crucial for radiance assimilation, were generated for the first time in India using CRTM to enable the assimilation of M2B radiances into the NGFS model. An Observing System Experiment (OSE) was conducted during the 2023 Indian summer monsoon season (May–August) to compare analyses with and without M2B radiance assimilation. The results demonstrate that assimilation of M2B radiances considerably reduced temperature and wind errors and improved mid‐tropospheric moisture, particularly over data‐sparse regions. These findings underscore the significance of M2B radiances in improving global NWP model performance in the tropics.