Text-to-Image
Text-to-image is the most common form of AI image generation. You write a text description and the AI creates a matching image. The quality of your prompt directly affects the quality of the image.
10 min•By Priygop Team•Updated 2026
How Text-to-Image Works
Text-to-image works in three stages:
- 1Text encoding: your text prompt is converted into a numerical representation that the model understands. This representation captures the meaning and relationships between words in your prompt.
- 2Image generation: the model starts from noise and gradually refines it into an image, guided at each step by the numerical representation of your text.
- 3Upscaling: many models enhance the resolution and detail of the final image to produce high-quality output.
Diagram
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Deep Learning ⊂ Machine Learning ⊂ Artificial Intelligence
Popular Text-to-Image Tools
- DALL-E 3 (OpenAI): available through ChatGPT Plus. Known for following prompts accurately and generating coherent images
- Midjourney: known for artistic quality and aesthetics. Used by many professional designers
- Stable Diffusion: open-source model that can run locally on your own computer. Highly customizable
- Adobe Firefly: integrated with Adobe Creative Cloud. Designed for commercial use with copyright-safe training data
- Google Imagen: Google's image generation model, available through Google products and Vertex AI
Key Takeaways
- Text-to-image is the most common form of AI image generation.
- DALL-E 3 (OpenAI): available through ChatGPT Plus. Known for following prompts accurately and generating coherent images
- Midjourney: known for artistic quality and aesthetics. Used by many professional designers
- Stable Diffusion: open-source model that can run locally on your own computer. Highly customizable