A model evaluation method, comprising: obtaining M first audio signals synthesized by using a first to-be-evaluated speech synthesis model, and obtaining N second audio signals generated through recording; performing voiceprint extraction on each of the M first audio signals to obtain M first voiceprint features, and performing voiceprint extraction on each of the N second audio signals to obtain N second voiceprint features; clustering the M first voiceprint features to obtain K first central features, and clustering the N second voiceprint features to obtain J second central features; counting cosine distances between the K first central features and the J second central features to obtain a first distance; and evaluating the first to-be-evaluated speech synthesis model based on the first distance; wherein M, N, K and J are positive integers greater than 1, M is greater than K, and N is greater than J; characterized in that the step of counting the cosine distances between the K first central features and the J second central features to obtain the first distance comprises: for every first central feature, calculating the cosine distance between the first central feature and each of the second central features to obtain J cosine distances corresponding to the first central feature, and calculating a sum of the J cosine distances corresponding to the first central feature to obtain a cosine distance sum corresponding to the first central feature; and calculating a sum of the cosine distance sums corresponding to the K first central features to obtain the first distance; wherein the step of evaluating the first to-be-evaluated speech synthesis model based on the first distance comprises: in the case where the first distance is smaller than a first preset threshold, determining that the evaluation of the first to-be-evaluated speech synthesis model is successful; and in the case where the first distance is greater than or equal to the first preset threshold, determining that the evaluation of the first to-be-evaluated speech synthesis model is not successful. obtaining M first audio signals synthesized by using a first to-be-evaluated speech synthesis model, and obtaining N second audio signals generated through recording; performing voiceprint extraction on each of the M first audio signals to obtain M first voiceprint features, and performing voiceprint extraction on each of the N second audio signals to obtain N second voiceprint features; clustering the M first voiceprint features to obtain K first central features, and clustering the N second voiceprint features to obtain J second central features; counting cosine distances between the K first central features and the J second central features to obtain a first distance; and evaluating the first to-be-evaluated speech synthesis model based on the first distance; wherein M, N, K and J are positive integers greater than 1, M is greater than K, and N is greater than J; characterized in that the step of counting the cosine distances between the K first central features and the J second central features to obtain the first distance comprises: for every first central feature, calculating the cosine distance between the first central feature and each of the second central features to obtain J cosine distances corresponding to the first central feature, and calculating a sum of the J cosine distances corresponding to the first central feature to obtain a cosine distance sum corresponding to the first central feature; and calculating a sum of the cosine distance sums corresponding to the K first central features to obtain the first distance; for every first central feature, calculating the cosine distance between the first central feature and each of the second central features to obtain J cosine distances corresponding to the first central feature, and calculating a sum of the J cosine distances corresponding to the first central feature to obtain a cosine distance sum corresponding to the first central feature; and calculating a sum of the cosine distance sums corresponding to the K first central features to obtain the first distance; wherein the step of evaluating the first to-be-evaluated speech synthesis model based on the first distance comprises: in the case where the first distance is smaller than a first preset threshold, determining that the evaluation of the first to-be-evaluated speech synthesis model is successful; and in the case where the first distance is greater than or equal to the first preset threshold, determining that the evaluation of the first to-be-evaluated speech synthesis model is not successful. in the case where the first distance is smaller than a first preset threshold, determining that the evaluation of the first to-be-evaluated speech synthesis model is successful; and in the case where the first distance is greater than or equal to the first preset threshold, determining that the evaluation of the first to-be-evaluated speech synthesis model is not successful.