To further enhance accuracy and reduce reliance on standard spectra and preset models, a novel γ spectrum quantitative method based on fuzzy C-means Gaussian mixture clustering (FCGMM) is proposed for low-activity environmental samples. The FCGMM algorithm was utilized to analyze the activities of 226Ra, 232Th and 40K in three soil reference samples and 238U, 235U and 232Th in five water reference samples, respectively, as measured by the HPGe γ spectrometer (GMX40P). To compare against the Gaussian fitting method (1.73%~14.99%, 8.59% on average) and the first derivative method (2.67%~16.29%, 9.81% on average) by calculating the relative errors, the FCGMM algorithm reduced relative errors by 1.87%~144.15% and 9.81%~173.61%, as well as average relative errors by 50.17% and 56.37%, respectively. For activities below 40 Bq, the FCGMM algorithm demonstrated significantly higher accuracy. The results indicate that the presented method can serve as a reference in low-activity γ spectrum analysis, providing rapid and accurate performance without the need of preset models.