The invention discloses an evaluation method of an electric energy meter manufacturer based on a metering big data clustering model, which comprises the following steps: acquiring the original data ofthe electric energy meter and screening the evaluation index of the quality of the electric energy meter; Gaussian mixture model clustering algorithm is used to extract the typical evaluation index data and obtain the clustering center to form the decision matrix of comprehensive quality evaluation of watt-hour meter, which is standardized according to the benefit type and cost type respectively.Based on the weight of AHP, entropy method, Pearson correlation coefficient method and variation coefficient method, the combination weights are obtained by the combination optimization model of index weights, and the decision matrices are weighted to obtain the comprehensive evaluation matrices of the quality of electric energy meters. The quality of watt-hour meter is evaluated comprehensivelyby the method of clip angle measurement, and the quality of each watt-hour meter supplier is sorted from high to low, and the evaluation results are obtained. It can provide support for accurate accounting of energy consumption and energy revenue.