GPT Image 2.5 workflow
How to create and edit images with GPT Image 2.5
A practical Image 2.5 tutorial: choose the right variant, structure prompts for text-to-image or image-to-image, lock output settings, then inspect and refine — all in the on-site Create workspace.
Related search topics
- GPT Image 2.5 tutorial
- Image 2.5 how to
- text to image
- image to image
- AI prompt
- Flare workflow
- Sunburst workflow
- 4K export
01
Choose Sunburst or Flare
Pick Flare for fast exploration and social-ready frames. Switch to Sunburst when product labels, fabrics, faces, or layout text must stay more consistent during AI image editing.
02
Add a prompt and visual references
For text-to-image, describe subject, style, lighting, and purpose. For image-to-image, upload references and state what must change vs what must stay — this is the fastest path to brand-safe edits.
03
Set size, quality, and format
Choose aspect ratio and resolution (including higher settings toward 4K when available), then quality from draft to max/auto. Export-friendly PNG / JPEG / WebP options may apply.
04
Generate, inspect, and refine
Check typography, materials, layout, and identity. Iterate with a tighter prompt or another reference instead of restarting the whole GPT Image 2.5 job.
Most “how to use Image 2.5” searches fail on vague prompts. Name the subject, camera/framing, materials, and the job (ad hero, portrait, poster). Add --style or negative notes only after the base brief is clear.
If results drift, reduce conflicting style words, attach 1–3 references, and change one variable per turn. That pattern works for AI image generator workflows and for precise retouching alike.
Next, browse creative use cases for industry examples, or open Create to run your first GPT Image 2.5 prompt on this portal.
FAQ
Do I need references for every GPT Image 2.5 job?
No. Pure text-to-image is fine for concepts. Add references when product shape, face identity, or brand layout must stay recognizable.
Why did my Image 2.5 result ignore part of the prompt?
Conflicting styles or too many goals in one line are common. Split into generate → inspect → refine turns, and put must-keep details first.