Abstract: Crop models are widely used in agricultural impact studies. However, many studies have reported large uncertainties from single-model-based simulation analyses, suggesting the need for multi-model simulation capabilities. In this study, the APSIM-Nwheat model was integrated into the Decision Support System for Agro-technology (DSSAT), which already includes two wheat models, to create multi-model simulation capabilities for wheat cropping systems analysis. The new model in DSSAT (DSSAT-Nwheat) was evaluated using more than 1000 observations from field experiments of 65 treatments, which included a wide range of nitrogen fertilizer applications, water supply (irrigation and rainout shelter), planting dates, elevated atmospheric CO2 concentrations, temperature variations, cultivars, and soil types in diverse climatic regions that represented the main wheat growing areas of the world. DSSAT-Nwheat reproduced the observed grain yields well with an overall root mean square deviation (RMSD) of 0.89 t/ha (13%). Nitrogen applications, water supply, and planting dates had large effects on observed biomass and grain yields, and the model reproduced these crop responses well. Crop total biomass and nitrogen uptake were reproduced well despite relatively poor simulations of observed leaf area measurements during the growing season. The low sensitivity of biomass simulations to poor simulations of leaf area index (LAI) were due to little changes in intercepted solar radiation at LAI >3 and water and nitrogen stress often limiting photosynthesis and growth rather than light interception at low LAI. The responses of DSSAT-Nwheat to temperature variations and elevated atmospheric CO2 concentrations were close to observed responses. When compared with the two other DSSAT-wheat models (CERES and CROPSIM), these responses were similar, except for the responses to hot environments, due to different approaches in modeling heat stress effects. The comprehensive evaluation of the DSSAT-Nwheat model with field measurements, including a comparison with two other DSSAT-wheat models, created a multi-model simulation platform that allows the quantification of model uncertainties in wheat impact assessments.