Google DeepMind's researchers have developed SODA, an AI model that addresses the problem of encoding images into efficient latent representations. With SODA, seamless transitions between images and semantic attributes are made possible, allowing for interpolation and morphing across various image categories. Diffusion models have revolutionized visual synthesis, excelling in diverse tasks like image, video, audio, and text synthesis, planning, and drug discovery. While prior studies focused on their generative capabilities, this study explores the underexplored realm of diffusion models' representational capacity. The study comprehensively evaluates diffusion-based representation learning across various datasets and tasks, shedding light on their potential derived solely