GPT Image 2: How to Use It and Compare GPT Image 1
Try a controlled image edit in iMini
GPT Image 2 is an image-generation and editing model; using it starts with a text brief or a reference photo. Choose a workflow available to your account, describe one change and identify the details to preserve. If you are comparing it with GPT Image 1, test the same input and acceptance criteria rather than assuming a newer name guarantees a better image. This guide explains that process and separates model documentation from third-party access.
API status: distinguish a model from a product menu
Before integrating either model, check the current official model documentation and deprecation notices. A previously scheduled retirement date is not, by itself, proof of the current operational state. A third-party menu entry also does not establish backend routing or API availability. Confirm the supported model identifier with your provider and run a small request in your own account before planning production work.
Official references: GPT Image 2, GPT Image 1, and image prompting and model-status reference. Recheck the live documentation before integrating.
How to use GPT Image 2 for a controlled edit
Open a service that currently offers the required image workflow. Upload the source, request a single edit and list the face, label or product details that must stay consistent. Generate a small test, compare it with the source, and repair one issue at a time. API users should additionally check supported input formats, model identifiers and current limits in the official documentation.
Visual fidelity: compare the same crop
Use the same source image, prompt, and comparable settings. Inspect skin texture, material detail, reflections, and edges at 100% and at delivery size. This guide has not run a controlled benchmark, so it does not assign either model a measured quality advantage.
Typography: check the exact words
Give both workflows the same short, quoted text and layout. Count spelling errors, repeated words, missing characters, and unreadable letters. Check Japanese, Korean, or Chinese text separately when the campaign needs it. Neither a model name nor a successful sample guarantees correct labels.
Style consistency: evaluate a series
Reuse a reference and the same character or brand description across several outputs. Compare facial features, color, clothing, light, and layout; do not infer series-level consistency from a single attractive image.
Reference preservation: inspect what must not change
For an edit, list the face, logo, shape, color, or readable label details that must remain unchanged. Overlay or compare corresponding crops. OpenAI documents high-fidelity image inputs for GPT Image 2, but fidelity is not a promise that every detail stays identical.
Composition: test constraints, not adjectives
Specify the subject location, crop, empty space, and camera angle. Mark violations rather than assuming “more intelligent” composition. If product geometry matters, reject an attractive scene that changes it.
Prompt control: isolate one instruction
Ask for one local change and explicitly preserve the rest. Compare the first result and a narrow follow-up. Record unintended changes and retries. Results vary with the source, prompt, settings, and model version.
Real-World GPT Image 2 Use Cases
1. Branding & Marketing Design
- Ad banners
- Social media posters
- Creative Typography
- Consistent brand imagery
- Seasonal promotions
2. Travel Bullet Journals & Creative Journaling
- Sticker sheets
- Watercolor journal layouts
- Hand-drawn elements
- Scrapbook-style collages
3. Product Visualization
- E-commerce listings
- Lifestyle mockups
- Packaging design concepts
- Color variations
- Seasonal campaign visuals
4. Portrait & Lifestyle Photography
- Profile photos
- Influencer mockups
- Fashion photography
- Couple or family photos
5. Education, Blogging, and Content Creation
- Better diagrams
- Scene illustrations
- Concept visualizations
GPT Image 1 vs GPT Image 2: documented facts and test criteria
| Item | GPT Image 1 | GPT Image 2 |
|---|---|---|
| Documented role | Image generation and editing | Image generation and editing |
| API status | Deprecated; scheduled shutdown October 23, 2026 | Official model reference available; check current provider access |
| Image input fidelity | Supports low or high input_fidelity | High-fidelity inputs; omit input_fidelity in its API requests |
| Text and product accuracy | Check each required detail | Check each required detail |
| Quality, latency, and cost | Measure on your task and settings | Measure on the same task and comparable settings |
GPT Image 2 Prompts You Can Copy
If you found this comparison while searching for GPT Image 2 prompts, start with these practical examples. They are written for editing and production workflows, not just one-off image generation.
1. Background Change Prompt
"Replace the current background with a clean modern studio environment. Keep the main subject unchanged, preserve hair edges or product edges, match the lighting direction, add realistic shadows, and keep the final image natural."
2. Product Photo Cleanup Prompt
"Clean up this product image for an e-commerce listing. Keep the product shape, label, color, texture, and proportions exactly accurate. Remove background clutter, improve lighting, add a subtle shadow, and place it on a clean white or light gray background."
3. Portrait Retouch Prompt
"Retouch this portrait naturally. Preserve the person's identity, face shape, expression, skin texture, hairstyle, and clothing. Reduce small blemishes, soften harsh shadows, brighten the eyes slightly, and keep the result realistic."
4. Blog Thumbnail Prompt
"Turn this image into a clean blog thumbnail. Keep the main subject recognizable, simplify the background, improve contrast, and leave empty space on one side for a headline. Do not add text inside the image."
Editing examples: evaluate the same job fairly
For background replacement, inspect hair or product edges and contact shadows. For a portrait, reject identity changes. For product cleanup, verify the logo, label, material, and silhouette. For a thumbnail, check subject placement and space for a headline. These are acceptance tests for either workflow—not evidence that one model always wins.
Which workflow should you use?
For an existing GPT Image 1 API integration, review the deprecation notice and validate a supported alternative before the shutdown date. If using iMini, choose from the models currently available to your account and confirm the model selection. Keep prompts and source files so you can compare revisions. A new version number alone is not a reason to accept a less accurate image.
Conclusion: choose a verified workflow, not a promise
Use documented model facts to build your shortlist, then decide using realistic images, production constraints, and current access. This page does not claim measured speed, price, or accuracy wins without a controlled test.
Frequently asked questions
Has GPT Image 2 been released?
OpenAI has an official GPT Image 2 model page with the gpt-image-2-2026-04-21 snapshot. Availability in an account or third-party product still depends on that service.
Is GPT Image 1 still a good choice for a new API integration?
Check the live model page and deprecation notice before starting a new integration. If the endpoint is deprecated or retired, select a currently supported alternative and validate it with your own task. An older scheduled date is not a live service-status check.
Is GPT Image 2 always better at text or photo editing?
This guide does not establish an always-better result. Test the exact wording, source image, settings, and preservation rules that your task needs.
Does a preservation prompt guarantee unchanged faces or labels?
No. Review the actual output and reject changes to identity or factual product information.
Are API status and iMini availability the same?
No. API documentation describes OpenAI’s API. Check iMini’s current model menu and provider information for the workflow you use.
Compare a real editing task in iMini before choosing your workflow