•SSC is the major characteristic for assessing quality of fresh peaches.•Hyperspectral imaging was used to measure the SSC.•Different types of PLS models were established and compared, respectively.•The multi-region combination model was superior to local region models.•A robust and accurate model could be built using the data of multiple regions. Soluble solids content (SSC) is one of the most important factors determining the quality and price of fresh fruits. This study was carried out to compare the different models for more robust and accurate evaluation of SSC in ‘Pinggu’ peaches using hyperspectral imaging in the visible and near infrared spectral range (400–1000 nm). The local region models and multi-region combination model based on full wavelengths were established and compared by partial least squares, respectively. The results of model analysis showed that multi-region combination model was superior to local region models due to insensitivity to the variation of the local regions of interest. Then, four typical wavelength selection algorithms including Monte Carlo cross-validation, successive projections algorithm, competitive adaptive reweighted sampling and random frog were utilized to select the effective wavelengths (EWs) for rapid quantitative determination of SSC, respectively. It was found that random frog was the most effective algorithm for local region models and multi-region combination model in SSC analyses. Considering the practical industrial application, finally, different type of models developed based on EWs selected by random frog were applied to predict the SSC of whole ‘Pinggu’ peaches from new test samples. EW-multi-region combination model achieved the optimal prediction results with rp of 0.86 and RMSEP of 0.67. The overall results of this study revealed that the hyperspectral imaging coupled with effective wavelength selection can be used to non-invasively and fast measure the SSC of ‘Pinggu’ peaches and a more robust and accurate model could be established based on multi-region information rather than any local region. These results can provide a useful reference for global evaluation of the internal quality attributes of fresh fruits.