In recent years， deep learning has been widely used and achieved significant development in various fields. How to utilize deep learning to effectively manage the explosive increasing 3D models becomes a hot topic. This paper introduces the mainstream algorithms for deep learning based 3D model retrieval and analyzes the advantages and disadvantages according to the experimental performance. In terms of the retrieval tasks， 3D model retrieval algorithms are classified into two categories： （1） Model-based 3D model retrieval algorithms require that both query and gallery are 3D models. It can be further divided into voxel-based method， point cloud-based method and view-based method in regard of different representations of 3D models. （2） For 2D image-based cross-domain 3D model retrieval algorithms， the query is 2D image while the gallery is 3D model. It can be classified to 2D real image-based method and 2D sketch-based method. Finally， we analyze and discuss existing issues of deep learning based 3D model retrieval methods， and predict possible promising directions for this research topic.