# Text-to-Image

> Text-to-image is generating a picture from a written prompt, using a model trained to turn a description into pixels — or, in some tools, vectors.

Text-to-image is generating an image from a written prompt. Most tools are built on diffusion models, and the practical differences for designers are text rendering, vector output, style control, and the commercial license attached to the plan you generated on.

**Text-to-image is the task of generating a picture from a written prompt: you describe what you want and a model produces the image.** Nearly every production tool in the category is built on a [diffusion model](/glossary/diffusion-model), which starts from noise and removes it step by step, steered by your prompt.

For design work, the interesting differences are no longer about who renders the prettiest photograph. They are about text rendering, whether the output is pixels or editable vectors, how tightly you can pin a style across a set of images, and what license comes attached to the plan you generated on. Those four axes are exactly how [the best AI image generators in 2026](/guides/comparisons/best-ai-image-generators-2026) sorts the tools: [Ideogram](/tools/ideogram) for typography, [Recraft](/tools/recraft) for vectors and reusable brand styles, [Midjourney](/tools/midjourney) for art direction.

Prompting is a smaller lever than it was. Subject, setting, composition, and medium still belong in the prompt, but consistency now comes from mechanisms rather than words: a style reference image, a saved custom style trained on your own work, or a locked aspect ratio and seed. And the last step is legal, not creative — check what your plan grants before publishing, since some free tiers generate publicly and license nothing. Where generated images fit in the rest of a designer's stack is covered in the [Claude Design guide](/guides/design/claude-design-guide).

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_Source: https://agentscamp.com/glossary/text-to-image — Term on AgentsCamp._