GPT Image 2
What is GPT Image 2?
GPT Image 2 is OpenAI's April 2026 image generator and the model that finally renders text correctly inside images, across 50+ languages including Arabic, Japanese, Korean, and Cyrillic. If you have ever burned credits regenerating a poster because GPT Image 1.5 turned "Open Saturday" into "Opon Sotardey", this is the noticeable upgrade. The other thing OpenAI changed is the controls. The old quality presets are gone. You pick a resolution (1K, 2K, or 4K), and the price scales with it. The request shape is otherwise identical to GPT Image 1 and 1.5, so swapping models is a one-line change.
What's new in GPT Image 2
Legible text across 50+ languages
Multi-line headlines, short body copy, captions, and signage render correctly in Latin, Cyrillic, Arabic, Japanese, Korean, and more. The headline upgrade over GPT Image 1.5.
Resolution control replaces quality presets
Pick 1K, 2K, or 4K and pay per resolution. No more guessing which preset matches your output target. Same prompt, three rate-card lines.
Up to 16 reference images per call
Reference cap is 16 (100 MB each). Material, reflection, and lighting copy across more reliably than 1.5, useful for product shots and brand-locked sequences.
Tighter prompt adherence on multi-object scenes
Six- or seven-element prompts hold composition without collapsing into a generic still. Useful for product flat-lays, infographics, and ensemble character art.
Drop-in replacement for 1.5 jobs
Same parameter shape as GPT Image 1 and 1.5. Change the model name, keep the rest. Useful if you already have a queued pipeline calling 1.5.
Best for
Posters and packaging with real text
Useful for shop signage and FMCG mocks where the text is the point.
Pitch decks and one-pagers
Generate the hero visual and the supporting tile in the same call by reusing references, no separate Figma round trip.
Multilingual creative
Same prompt with different language strings produces matching layouts. Saves a localization pass in the design pipeline.
Brand campaign hero stills
4K output is enough for web banners and most print. Keep references locked across a campaign for consistent look.
Reference-driven product shots
Up to 16 reference photos per call. Material, reflection, and lighting copy across more reliably than 1.5.
Drop-in replacement for GPT Image 1.5 jobs
Same parameter shape. Change the model name, keep the rest. Useful if you have a queued pipeline already calling 1.5.
Use cases
Render a multilingual poster set in one batch. Same prompt, swap the language string, and GPT Image 2 renders legible copy in each writing system at 4K for print and 2K for web. Build packaging mocks where the SKU label has to read at thumb size: 1K covers the listing tile, 4K covers the press kit. A/B test pitch-deck heroes by passing 8 to 16 references per call and letting the model remix them into framed compositions for the slide. Migrate an existing GPT Image 1.5 pipeline by changing the model name and switching the old quality field to a resolution value.
API examples
Call GPT Image 2 from any language by POSTing to /v1/tasks. Full parameter docs live at docs.unifically.com/models/image/openai/gpt-image-2.
curl -X POST https://api.unifically.com/v1/tasks \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "openai/gpt-image-2",
"input": {
"prompt": "A serene mountain landscape",
"aspect_ratio": "1:1",
"resolution": "2K"
}
}'
Successful submission returns a task_id. Poll GET /v1/tasks/<task_id> or set a callback_url on the request to receive the finished result.
FAQs
People also ask
GPT Image 2 is OpenAI's April 2026 image model. It accepts a prompt, an output resolution (1K, 2K, or 4K), an optional aspect ratio, and up to 16 reference images per request. The big upgrades over 1.5 are accurate text rendering across 50+ languages and tighter prompt adherence on multi-object scenes.
Two practical changes. The old quality presets are gone, you pick a resolution (1K, 2K, 4K) and pay accordingly. And text inside images actually reads now, including non-Latin scripts. The request shape is unchanged so you can swap the model name and go.
Three ratios at every resolution: 1:1, 3:2, and 2:3. If you need 9:16 or 16:9 specifically, use Nano Banana Pro or SeeDream for wider aspect ranges.
Up to 16 reference images per request, each up to 100 MB. References are passed as URLs in the image_urls array on the same generate endpoint.
Yes if your prompts include readable text, posters, packaging, UI mockups, or multilingual signage. Yes if you need tight prompt adherence on multi-subject scenes.
