You might often hear people use the term “diffusion models” together with Stable Diffusion, which is the base AI technology that powers Stable Diffusion. Simply put, diffusion models generate images by starting with a pattern of random noise and gradually shaping it into a coherent image through a process that reversibly adds and removes noise. This process is computationally intensive but has been optimized in Stable Diffusion with latent space technology.
Latent space is like a compact, simplified map of all the possible images that the model can create. Instead of dealing with every tiny detail of an image (which takes a lot of computing power), the model uses this map to find and create new images more efficiently. It's a bit like sketching out the main ideas of a picture before filling in all the details.
In addition to static images, Stable Diffusion can also produce videos and 3D objects, making it a comprehensive tool for a variety of creative tasks.
Why should you use Stable Diffusion:
Multiple variants: Stable Diffusion comes with a variety of popular base models, such as Stable Diffusion 1.4, 1.5, 2.0, and 3.5 (Medium, Large and Turbo), Stable Diffusion XL, Stable Diffusion XL Turbo, and Stable Video Diffusion. They also provide optimized models for NVIDIA and AMD GPUs respectively.
According to this evaluation graph, the SDXL base model performs significantly better than the previous variants. Nevertheless, I think it is not 100% easy to say which model generates better images than others. This is because the results can impacted by various factors, like prompt, inference steps and LoRA weights. Some models even have more LoRAs available, which is an important factor when choosing the right model. For beginners, I recommend you start with SD 1.5 or SDXL 1.0. They're user-friendly and rich in features, perfect for exploring without getting into the technical details.
Customization and fine-tuning: Stable Diffusion base models can be fine-tuned with as little as five images for generating visuals in specific styles or of particular subjects, enhancing the relevance and uniqueness of generated images. One of my favorites is SDXL-Lightning, built upon Stable Diffusion XL; it is known for its lightning-fast capability to generate high-quality images in just a few steps (1, 2, 4, and 8 steps).
Points to be cautious about:
Note: See our blog post Stable Diffusion 3: Text Master, Prone Problems? to learn how it performs compared with SD 2 and SDXL and how you can improve its generated images.
Last modified 22 March 2026