💡 The paper introduces PhysForge, a system for generating interactive 3D assets that combines visual-language modeling with a physics-grounded diffusion model. The problem addressed is the lack of functional properties in existing methods for generating 3D assets, which focus on static geometry and overlook the need for interactive virtual worlds and embodied AI. To solve this, PhysForge uses a two-stage framework, first using a visual-language model to plan a hierarchical physical blueprint that defines material, functional, and kinematic constraints. Then, a physics-grounded diffusion model synthesizes high-fidelity geometry and precise kinematic parameters using a novel injection mechanism called KineVoxel Injection. The system is supported by PhysDB, a large-scale dataset of 150,000 assets with physical annotations. The results show that PhysForge produces functionally plausible and simulation-ready assets, providing a robust data engine for interactive 3D content and embodied agents. Overall, PhysForge contributes a new approach to generating physics-grounded 3D assets that can be used in interactive virtual worlds and embodied AI applications.