This repository presents VA-VAE and LightningDiT, addressing the optimization dilemma in latent diffusion models where reconstruction and generation objectives conflict. The work introduces a variational approach to balance reconstruction quality with generative capability, and proposes architectural optimizations for faster diffusion transformer training. It achieves competitive FID scores on ImageNet-256×256 image generation with significantly reduced computational requirements.