Unlike DALL-E and diffusion models, GPT Image 1.5 uses an autoregressive generation method built directly into GPT-4o — images are a native output, not a separate model call.

Refine images through natural conversation. The model remembers context across turns — describe a character, then iterate appearance, pose, and environment in separate follow-up messages.

GPT-4o's vast knowledge base informs every image — accurately representing landmarks, historical styles, brand guidelines, cultural contexts, and domain-specific visual accuracy.

Accurately renders legible text within images — significantly better than DALL-E models. Ideal for posters, mockups, marketing materials, and any design where in-image text must be readable.

Upload any image and use it as context — transform its style, extract elements, or use it as visual inspiration for new generations while maintaining thematic consistency.

Three quality levels (low / medium / high) at 2–15 credits let you balance speed, cost, and detail for every use case — rapid concept validation or high-fidelity final output.