Ouroboros3D is a unified 3D generation framework that integrates multi-view image generation and 3D reconstruction into a single recursive diffusion process. The framework jointly trains the two modules via a self-supervised mechanism, enabling them to adapt to each other and achieve robust inference. During multi-view denoising, the multi-view diffusion model utilizes 3D-aware rendered images from the reconstruction module at the previous timestep as additional conditioning. The combination of the recursive diffusion framework with 3D-aware feedback improves the overall geometric consistency of the process. Experiments demonstrate that the Ouroboros3D framework outperforms both separate training of the two stages and existing methods that combine them at inference time.