Diffusion models have emerged as powerful tools for molecular generation, particularly in the context of 3D molecular structures. These models, inspired by non-equilibrium statistical physics, can generate 3D molecular structures with specific properties crucial to drug discovery. This review focuses on the technical implementation of diffusion models tailored for 3D molecular generation, comparing their performance, evaluation methods, and implementation details. It covers strategies for atom and bond representation, architectures of reverse diffusion denoising networks, and challenges associated with generating stable 3D molecular structures. The review also explores the applications of diffusion models in de novo drug design and related areas of computational chemistry, such as structure-based drug design, molecular docking, and molecular dynamics of protein-ligand complexes. By summarizing the state-of-the-art diffusion models for 3D molecular generation, this review highlights their role in advancing drug discovery and their current limitations.Diffusion models have emerged as powerful tools for molecular generation, particularly in the context of 3D molecular structures. These models, inspired by non-equilibrium statistical physics, can generate 3D molecular structures with specific properties crucial to drug discovery. This review focuses on the technical implementation of diffusion models tailored for 3D molecular generation, comparing their performance, evaluation methods, and implementation details. It covers strategies for atom and bond representation, architectures of reverse diffusion denoising networks, and challenges associated with generating stable 3D molecular structures. The review also explores the applications of diffusion models in de novo drug design and related areas of computational chemistry, such as structure-based drug design, molecular docking, and molecular dynamics of protein-ligand complexes. By summarizing the state-of-the-art diffusion models for 3D molecular generation, this review highlights their role in advancing drug discovery and their current limitations.