Product ad creative
GPT-Image-2
Prompt: A matte green skincare serum bottle on travertine with eucalyptus, water droplets, soft morning light, and the headline “DEWY, NOT GREASY.”
OpenAI Typography Engine
GPT-Image-2: the image model that spells your headline right
OpenAI's next-generation image model pairs best-in-class text rendering with three quality tiers and resolutions to 4K — posters, packaging, and ads with words you can ship.
From 3 credits per image, based on quality and resolution.By OpenAI
Your generated image will appear here.
Enter a prompt and click 'Generate Image' — or start from an example:
Examples
GPT-Image-2 examples from real prompts
Explore generated GPT-Image-2 outputs, open any image for a closer look, and adapt the prompt to your own subject.
Poster and typography
GPT-Image-2
Prompt: A three-color screen-print jazz poster with a double bass silhouette, burnt-orange sun, halftone texture, and exact event copy.
LinkedIn headshot
GPT-Image-2
Prompt: A professional corporate headshot with natural window light, an 85mm lens look, realistic skin texture, and a softly blurred modern office.
Pixel art
GPT-Image-2
Prompt: A tiny ramen shop on a rainy Tokyo side street at night in crisp, limited-palette, SNES-era pixel art.
Detailed illustration
GPT-Image-2
Prompt: An isometric cutaway of a cozy two-story bookshop cafe with readable room details, warm afternoon light, readers, plants, and a sleeping cat.
Travel and fashion portrait
Vintage transit summer portrait
Prompt: A realistic vertical travel-fashion portrait of an adult East Asian woman beside an open vintage train window, with wind-swept hair, bright natural sunlight, a pale ivory tie-front top, deep indigo denim shorts, shallow depth of field, natural anatomy, and a fresh nostalgic summer mood.
What makes GPT-Image-2 a typography engine?
GPT-Image-2 is OpenAI's next-generation image model, and its signature skill is setting text: headlines, labels, and packaging copy that arrive spelled as written and laid out as if a designer placed them.
On RenderFlow AI you steer it with three quality tiers (Low, Medium, High), ten aspect ratios from 1:1 to 21:9, and three resolutions (1K, 2K, 4K) — so a draft poster costs as little as 2 credits while a 4K High final tops out at 72.
Why GPT-Image-2 leads with its typography
Copy you can ship unedited — Most image models treat words as decoration; GPT-Image-2 typesets them. Event posters, sale signage, and product labels come back with the headline intact, which removes the usual "fix the text in Figma" step.
Copy you can ship unedited — Most image models treat words as decoration; GPT-Image-2 typesets them. Event posters, sale signage, and product labels come back with the headline intact, which removes the usual "fix the text in Figma" step.
Layouts that follow the brief — Multi-part instructions — logo top-left, product center, three benefit callouts along the bottom — land where you asked. That makes it the rare image model usable
Layouts that follow the brief — Multi-part instructions — logo top-left, product center, three benefit callouts along the bottom — land where you asked. That makes it the rare image model usable for structured ad formats, not just open-ended art.
Three tiers, mapped to stages — Low at 2–3 credits is a sketching tier, Medium (6–18) covers most production work, and High (22–72) is reserved
Three tiers, mapped to stages — Low at 2–3 credits is a sketching tier, Medium (6–18) covers most production work, and High (22–72) is reserved for finals. The wide price spread means you only pay premium rates on approved layouts.
Ten frames from square to cinematic — The aspect-ratio list runs from 1:1 through 4:5 and 3:4 up to 21:9, covering feed tiles, story formats, and banner crops in one model. Pick the frame first and GPT-Image-2 composes to it.
Ten frames from square to cinematic — The aspect-ratio list runs from 1:1 through 4:5 and 3:4 up to 21:9, covering feed tiles, story formats, and banner crops in one model. Pick the frame first and GPT-Image-2 composes to it.
Formats where GPT-Image-2's text holds up
- AI image generation with text elements
- Marketing and social media graphics
- Posters, ads, and branded content
- Product concepts and visual exploration
A tiered GPT-Image-2 poster workflow
Choose the frame from ten ratios
Match the placement first: 4:5 or 1:1 for feed ads, 9:16 for stories, 3:2 or 16:9 for web banners, 21:9 for cinematic headers. GPT-Image-2 plans its layout around the ratio you pick.
Write the copy in quotes, then the art direction
List exact strings first — "SPRING SALE", "50% OFF THIS WEEKEND" — with a placement note for each, then describe imagery, palette, and style. Separating copy from art direction is how both survive.
Sketch the layout on Low at 1K
At 2 credits, Low/1K output is disposable: check whether the headline landed, the layout reads, and the product is recognizable. Expect to throw these away — that is what the tier is for.
Climb the tiers only after the layout works
Medium at 2K (10 credits) covers most publishing needs; High at 4K (72) is for print-adjacent finals and client presentations. Raise resolution before quality — a bigger Medium usually beats a smaller High for legibility checks.
Proofread at 100% before export
Zoom in and read every line. If one string is wrong, shorten it or reduce the number of text elements and regenerate at the same settings — and keep the winning prompt, because it is reusable next campaign.
Frequently Asked Questions
How do GPT-Image-2's quality tiers map to credits?
Low costs 2 credits at 1K, 2 at 2K, and 3 at 4K. Medium costs 6, 10, and 18 respectively. High costs 22, 40, and 72. Sketch on Low, produce on Medium, and reserve High for finals that need maximum polish.
What aspect ratios and resolutions does GPT-Image-2 support?
Ten aspect ratios — 1:1, 16:9, 9:16, 3:2, 2:3, 4:3, 3:4, 4:5, 5:4, and 21:9 — at three resolutions: 1K, 2K, and 4K. Quality tier and resolution multiply together, so High at 4K is the most expensive combination.
How do I get accurate text in a GPT-Image-2 poster?
Put each line of copy in quotes, state where it sits ("headline across the top third"), and keep individual strings short. Then proofread the output at full size — GPT-Image-2 is best in class for text, not infallible.
GPT-Image-2 vs GPT-Image-1 — should I switch?
GPT-Image-2 adds 2K and 4K resolutions, ten aspect ratios instead of three fixed sizes, and stronger text and detail rendering. GPT-Image-1 remains a capable budget option at 2/7/26 credits for its low/medium/high tiers.
GPT-Image-2 or Seedream V4 for poster work?
GPT-Image-2 wins on copy accuracy and tiered quality control; Seedream V4 counters with custom canvas sizes up to 4096px per side at a flat 5 credits. For an important campaign, run a headline test on both.
When does GPT-Image-2 text still fail?
Very long strings, many separate text elements, and footnote-sized copy are the usual failure points. Split dense layouts into fewer lines, shorten the copy, or regenerate with a simplified structure.
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