This study was to systematically investigate the effect of mobile phase additives, including ammonia water, formic acid, acetic acid, ammonium chloride and water (as a control), on qualitative and quantitative analysis of fifteen representative ginsenosides based on liquid chromatography hybrid quadrupole-time of flight mass spectrometry (LC–Q-TOF/MS). To evaluate the influence of mobile phase additives on qualitative performance, the quality of the negative mode MS/MS spectra of ginsenosides produced by online LC–Q-TOF/MS analyses, particularly the numbers and intensities of fragment ions, were compared under different adduct ion states, and found to be strongly affected by the mobile phase additives. When 0.02% acetic acid was added in the mobile phase, the deprotonated ginsenosides ions produced the most abundant product ions, while almost no product ion was observed for the chlorinated ginsenoside ions when 0.1mM ammonium chloride was used as the mobile phase additive. On the other hand, sensitivity, linear range and precision were adopted to investigate the quantitative performance affected by different mobile phase additives. Validation results of the LC–Q-TOF/MS-based quantitative performance for ginsenosides showed that ammonium chloride not only provided the highest sensitivity for all the target analytes, but also dramatically improved the linear ranges, the intra-day and inter-day precisions comparing to the results obtained using other mobile phase additives. Importantly, the validated method, using 0.1mM ammonium chloride as the mobile phase additive, was successfully applied to the quantitative analysis of ginsenosides in rat plasma after intragastric administration of Ginsenoside Extract at 200mg/kg. In conclusion, 0.02% acetic acid was deemed to be the most suitable mobile phase additive for qualitative analysis of ginsenosides, and 0.1mM ammonium chloride in mobile phase could lead to the best quantitative performance. Our results reveal that choosing the appropriate mobile phase additive is an important step in optimizing the analytical conditions, and the best quantitative method may not be suitable for the qualitative analysis.