Modern neural networks have learned to create images that increasingly resemble the work of professional illustrators. But what happens when the same idea is given to different models? This experiment shows how each neural network interprets text in its own way—with its own style, composition, and visual thinking.
We took the same request: “a small cafe on a Paris street, a warm evening, neon signs, soft lighting, cinematic style.” The goal was to compare how five popular image generators convey atmosphere and detail.
Stable Diffusion was the starting point. It remains the most flexible model that can be installed locally and fully controlled. The result was warm and realistic: soft lighting, reflections in shop windows, atmospheric perspective. The model handles textures and architecture very well, especially in the SDXL version. However, the composition sometimes seems a little static — the neural network prefers symmetry and safe angles. If you add ControlNet and LoRA, you can achieve the level of artistic cinema, but the basic generation still remains recognizable.
Midjourney, on the other hand, turns the same request into a work of art. Here, the cafe is shrouded in haze, the signs glow a little brighter, and the colors are more saturated. Each frame looks like it was shot on an old movie camera with soft focus. Midjourney adds a visual “signature” — textures become almost painterly, lines blur, and everything looks expensive and atmospheric. But beauty comes at the price of control: the model does not accurately convey the exact pose of a person or the inscription on a sign. It is a tool for emotions, not technical accuracy.
DALL·E 3, built into ChatGPT and Bing, proved to be the most accurate in understanding text. It literally reads every word. If you mention “a red sign with the inscription Café Lumière” in the description, DALL·E will actually draw it — and without spelling mistakes. The result looks clean and almost advertising-like: neat shapes, balanced colors, correct perspective. This generator is ideal for brand visualizations and infographics, but sometimes it lacks “soul” — the image is too correct, like something out of a catalog.
Adobe’s Firefly approached the task with designer precision. The generator focuses on composition and lighting, producing results that look like they came straight out of an interior design magazine. Pleasant tones, smooth gradients, and clever light distribution. Firefly is especially useful for those who work in the Adobe ecosystem: images can be edited immediately in Photoshop or Illustrator. However, as with DALL·E, there is a sense of corporate restraint — the model tries to avoid bold decisions and produces visuals that fit perfectly into an advertising layout but rarely surprise.
Leonardo AI was the most unexpected participant. Its result looks like a frame from a modern movie. It accurately conveys the atmosphere of a “neon evening,” adding depth, dynamics, and texture. There is a sense of movement in its composition — passers-by, rain, reflections. Leonardo is often used in game development and concept art, and it shows: the image is not just beautiful, but alive. It works best with realistic scenes and stylish contrasts, creating the feeling of a finished frame for a trailer.
Five generators — five characters. Stable Diffusion is flexible and technically controlled, Midjourney is emotional and cinematic, DALL·E is logical and accurate, Firefly is design-balanced, and Leonardo is visually powerful and atmospheric. The same text has turned into five completely different worlds.
This experiment demonstrates that neural networks are no longer just tools, but full-fledged co-authors. Each has its own “sense of taste” and style, just like artists. The choice of generator now depends not on who draws better, but on what character you need for your visual. Stable Diffusion is suitable for complete control and experimentation, Midjourney is for emotions and inspiration, DALL·E is for precise task execution, Firefly is for design, and Leonardo is for visual wow effect.