To rapidly identify the compound Yiganling tablets from different manufacturers by near-infrared fibre-opti-cal spectroscopy and detect the content of silymarin. Methods:The ninety-three batches of compound Yiganling tablets from six manu-facturers were used as the analysis objects. Clustering analysis model of compound Yiganling tablets was established. The spectra were pretreated with the second derivative and vector normalization;the number of smoothing point was thirteen; the wavelength range was 9 000-4 100 cm-1;the distance between the spectra was Euclidean distance, the distance between the spectra and the class was the sum of square of the variance(Ward’s method). The quantitative model was established using the same samples. The spectra were pretreated with the first Derivative and vector normalization;the number of smoothing point was seventeen;the wavelength ranges were 9 100-7 300 cm-1 and 7 100-4 100 cm-1;the regression method was partial least squares ( PLS) algorithm. Results:The clustering model could identify the samples of training set, and validate the thirty spectra of test set accurately. For the quantitative model of the content of silymarin, the root mean square error of cross validation (RMSECV) was 0. 082 8 and the determination coefficient R2 was 97. 98%. The root mean square error of prediction (RMSEP) was 0. 044 1 and the correlation coefficient R2 was 98. 95%. Conclu-sion:The clustering analysis and the quantitative model are rapid and simple, accurate and reliable, and can be applied in fast drug a-nalysis.