The single iteration path of the clustering algorithm limits the search path of the parameter’s optimal value. In this paper, a multi-path Gaussian kernel fuzzy c-means clustering method is proposed and named MGKFCMs. Firstly, MGKFCMs takes the nuclear objective function and the fuzzy membership degree function in the kernel function as the Gaussian kernel function. Secondly, the gradient method is used to get the iterative formula of the clustering center. Based on this iterative formula and particle swarm optimization algorithm, the parameters of the clustering center are calculated iteratively in parallel. In every iteration of clustering, a path with small clustering objective function value is selected as the final path of parameter iteration. The correlation property of MGKFCMs is analyzed, and the convergence of the algorithm is studied. Simulation results show that the proposed algorithm is effective.