Text to image generative models are AI models trained on large datasets of images paired with textual descriptions. They learn to translate text prompts into realistic or artistic images by understanding both visual content and language structure.
Stable Diffusion, Midjourney, and DALL-E are currently the most popular and widely used text-to-image generative models in many industries allthow there are many others on the market.
Here is a classification of text-to-image models based on the purpose they best serv.
The reason Stable Diffusion, Midjurney, and DALL-E are the most popular and most used models on the market is that each offers a unique balance of accessibility, quality, flexibility, and community support—filling different creative and professional needs.
To begin with, DALL-E is built on ChatGPT ( pro users) and this makes it extremely familiar, intuitive in usage bringing seamless integration with text conversation and AI assistance. It is user friendly and very strong in rendering real-world scenes, human figures, and specific items from prompts. It’s unique strengths are direct photo editing (inpainting), easily innterpreting complex prompts and filtering results according to audience ( comercial general audience vs professionals)
On the other hand Midjurney is ideal for concept art, moodboards and fantasy scenes, presenting the user with fast iterations- upscale, remix, or vary any image with one click. It’s popularity comes from its stunning, artistic results, its results being considered the most aesthetically pleasing and stylized images out of the box. Adding to that is the fact that it can transform even vague prompts into beautiful results. Last but not least, the Discord community attached to it is very easily to join, very eager to share and give feedback wich is very useful and accelerates learning and performance.
The top feature that makes Stable Diffusion stand out is the full customisation possibilities, a quality most appreciated by the more technical creative industries like architecture and design. It supports training, fine-tuning, custom styles (via LoRA, DreamBooth), that make a higer grade of precision posible. It works with tools like ComfyUI, Automatic1111, and ControlNet for deep control. The user should also take into consideration the flexible workflow supported by Stable Difussion, the fact that it is open source and free and also the possibility of working offline that is great for privacy and enterprise settings. The photorealism of the images generated on this model as well as the high grade of control, differentiate Stable Diffusion from DALL-E and Midjurney and makes itideal for architecture,interior design, product design, and photorealistic projects.