A novel, efficient, and accurate fingerprinting method using high performance liquid chromatography-photodiode array detection has been developed and optimized for the investigation and demonstration of the variance in chemical properties among Siraitia grosvenorii fruits from different origins. The effects of growth stages, cultivated varieties, collection locations, and fruit portions of the herb on chromatographic fingerprints were examined. Eleven compounds were identified on chromatograms by comparing the retention time and UV spectrum of each peak separately with those of external references. The results revealed that chromatographic fingerprints, combining similarity or hierarchical clustering analysis along with reference compounds, could efficiently identify and distinguish S. grosvenorii fruits from different sources, which provided helpful clues for studying the plants' secondary metabolites and benefitted quality control.