MeshDiffusion implements a score-based generative model for creating 3D meshes. The approach leverages deep marching tetrahedra (DMTet) to directly parameterize and generate 3D shapes. It builds on diffusion model principles but applies them to the 3D geometry domain, enabling high-quality mesh generation across categories like chairs, cars, airplanes, and tables at multiple resolutions.