SAM-guided Graph Cut for 3D Instance Segmentation is a deep learning approach utilizing 3D geometry and multi-view image information for 3D instance segmentation. By employing a 3D-to-2D query framework, this method effectively leverages 2D segmentation models to perform 3D instance segmentation, constructing a superpoint graph through graph cut problems and training via graph neural networks to achieve robust segmentation performance across diverse scene types.