This thesis aims to investigate the promising Diffusion Models (DMs) technology by developing a prototype that meets the requirements for variability and quality of generated images. The ultimate goal is to initiate the technology transition by exploring DMs in conjunction with the well-established StyleGAN. Through this work, I specifically examine the behavior of DMs in the "Color to Image" task and their ability to generate images based on color label conditioning with the final goal of producing 512x512 resolution images. I adopt a step-by-step approach to gain a thorough understanding of this new technology, both practically and theoretically. Understanding how I can effectively condition a diffusion model to enable precise control over the generative process was an essential step.