Objective: To establish a method combining high performance liquid chromatography (HPLC) fingerprint with quantitative analysis of multi-components with a single marker (QAMS), for simultaneous determination of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, cynaroside, isochlorogenic acid B, isochlorogenic acid A,isochlorogenic acid C, buddleoside, rupestonic acid, chrysosplenetin and artemisetinin Artemisia rupestris L.. The comprehensive quality evaluation model of different producing areas was established to provide reference for the overall quality evaluation. Methods: HPLC method was used to determine the fingerprints of 15 batches of Artemisia rupestris L. from different origin. Stationary phase was YMC-Pack ODS-A C18 column (250 mm×4.6 mm, 5 μm)was adopted, and the mobile phase was acetonitrile-water (containing 0.2% formic acid) with gradient elution, the detection wavelength was segmented changes, the column temperature was 30℃, the flow rate was 1.0 mL·min^-1.The information of fingerprinting spectrum was analyzed by cluster analysis (CA), principal component analysis (PCA) and orthogonal partial least-squares discrimination analysis (OPLS-DA). At the same time,the entropy weight technique for order preference by similarity to ideal solution (EW-TOPSIS), the weighted rank sum ratio (WRSR) and the fuzzy combination of the two methods to construct the evaluation model. With buddleoside as the internal standard, the relative correction factors (RCF) of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, cynaroside, isochlorogenic acid B, isochlorogenic acid A, isochlorogenic acid C,rupestonic acid, chrysosplenetin and artemisetin were determined and their contents were calculated to establish QAMS method. Results: A total of 18 common peaks were calibrated and ten of them were identified by the established fingerprint of Artemisia rupestris L.. The study of stoichiometric model showed that there were obvious differences among different producing areas of Artemisia rupestris L.. Eleven different components were selected by OPLS-DA method. The comprehensive quality evaluation model of EW-TOPSIS method, WRSR method and their fuzzy combination showed the consistent quality evaluation ranking results of different producing areas. The resolution and linear relationship of ten components in quantitative analysis were good. The average recovery rates were 92.6%-107.2% with RSD<3.0%. There was no significant difference between the results of QAMS with chlorogenic acid as internal standard and the results of external standard (P>0.05). Conclusion: The established HPLC fingerprint combined with QAMS method is simple, reliable and has good repeatability. The results of the comprehensive quality evaluation model established are comprehensive and objective, which can be used to evaluate the overall quality of Artemisia rupestris L..