Face quality evaluation can filter out low quality face image to save computational resources and improve the system performance, labeling the face image quality score by manual consume too much manpower. To solve this problem, an unsupervised face image evaluation based on face recognition is proposed. We use the face recognition model to calculate the features of faces and label the images quality score. The face recognition model is compressed by knowledge distillation method to obtain efficient quality assessment model. Experimental results show that this method can effectively evaluate the quality of face image and improve the performance of face recognition.