Image generationdefinition and how it works in 2026
- Image generation
- The broader category of AI-generated images — includes text-to-image, image-to-image (editing), inpainting, outpainting, and style transfer. Powered by diffusion models or transformer-based image generators.
Image generation is the umbrella term for any AI-driven image creation. Text-to-image is one mode; others include image-to-image (modify an existing image based on a prompt), inpainting (fill in masked regions), outpainting (extend an image beyond its borders), and style transfer (apply one image's style to another).
In 2026 the technology stack is mature: diffusion models dominate for image generation (Stable Diffusion, Flux, Midjourney internals), with transformer-based models gaining ground (Gemini 2.5's native image generation, GPT-image-1). Most consumer products combine both under the hood.
For agent builders, image generation enables agents to create visual deliverables (marketing collateral, product mockups, illustrations) without human design intervention. Integration is typically via API: send a prompt, get an image URL.
Where this shows up
Frequently asked
What is the difference between image generation and text-to-image?+
Text-to-image is one mode of image generation. Image generation also includes image-to-image (modify existing), inpainting (fill masked regions), outpainting (extend), and style transfer.
Can AI generate consistent character images?+
Yes with care. Use IP-Adapter-style techniques, character LoRAs, or seed locking. Frontier models (Midjourney v7 character mode, Flux) ship with character consistency features built in.
