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GPT-4o image generation became notable for following detailed visual instructions, rendering text more reliably than many earlier image tools, accepting reference images, and supporting conversational revisions. The product label has since changed: OpenAI retired GPT-4o from ChatGPT on February 13, 2026, while ChatGPT Images continued as a separate image-generation experience. OpenAI’s current help documentation covers ChatGPT Images 2.0, and its developer documentation currently points new API image-generation builds toward GPT Image 2.
The prompts below use the capabilities that matter most across current image-generation workflows: a clearly described subject, spatial relationships, composition, lighting, style, exact text, aspect ratio, reference images, and small follow-up edits. Treat “GPT-4o” in the title as the familiar name for this style of prompting—not as a promise that every example will behave identically in every current model or ChatGPT plan.
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How to get better results from these prompts
Describe the image you want to see rather than only naming an end result. “Make a beautiful product image” leaves important decisions open. A stronger prompt identifies the object, its material, its surroundings, the light source, the camera viewpoint, the composition, and the intended use.
OpenAI’s prompting guidance recommends clear, specific instructions with enough context. For image generation, that usually means:
- Subject: Say exactly what should appear.
- Relationships: Explain what is in front, behind, beside, above, or inside something else.
- Hierarchy: Identify the focal point and tell the model which details are secondary.
- Visual treatment: Specify medium, style, color palette, lighting, and texture.
- Composition: Include framing, viewpoint, orientation, negative space, and aspect ratio when they matter.
- Constraints: State what must not change or what should be left out.
These are starting points, not guaranteed one-click recipes. Image generation is probabilistic. Review the result, identify the most important problem, and make one or two targeted changes instead of rewriting the entire prompt every time.
1. Editorial product hero image
Create a clean editorial product photograph of a matte cobalt-blue insulated travel mug on a pale stone pedestal, morning window light from the left, soft realistic shadow, a few coffee beans in the background, premium lifestyle-advertising composition, generous negative space on the right for headline text, landscape 3:2.
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This prompt works because it combines the subject, surface, color, light direction, supporting objects, intended composition, and output shape. The phrase “negative space on the right” is more useful than simply asking for a “professional” image: it tells the model where a later headline may go.
2. Children’s-book scene
Create a warm children’s-book illustration of a small red fox delivering a letter through a snowy village at dusk. Include six warmly lit cottages, a wooden footbridge, falling snow, and one brass mailbox in the foreground. Keep the fox as the clear focal point, with a gentle watercolor-and-gouache texture and a portrait composition.
Object counts can help control a busy scene. The prompt also establishes a subject hierarchy: the fox is the focal point, while the cottages, bridge, snow, and mailbox support the story.
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3. Four-step infographic
Design a readable four-step infographic titled ‘How Rainwater Reaches a Garden.’ Use four horizontally arranged panels: roof, gutter, storage barrel, and vegetable bed. Use a navy, teal, cream, and yellow palette; simple labeled arrows; consistent icon style; high contrast; no extra text beyond the title and the four step labels; wide 16:9 layout.
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Diagrams and infographics require more than a subject description. Specify the number of panels, their order, labels, palette, typography constraints, and layout. OpenAI’s image-model prompting guide identifies structured visuals such as diagrams and infographics as important use cases.
Inspect every label manually. Even improved text rendering can produce a misspelling, an incorrect arrow, or a layout that is technically attractive but difficult to read.
4. Character consistency across revisions
Create a cinematic character portrait of Mina, a fictional 32-year-old marine biologist with short curly black hair, round amber glasses, a yellow rain jacket, and a teal backpack, standing on a stormy research pier. Keep her facial features, clothing colors, and backpack consistent in every revision. Natural overcast light, realistic editorial photography, medium shot.
Then try a focused follow-up edit:
Keep Mina, her face, jacket, backpack, and lighting unchanged. Move the camera farther back and show the full pier.
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The first prompt establishes identity anchors. The second changes one major variable—camera distance—while explicitly protecting the details you want preserved. Conversational image workflows are particularly useful when you want to refine a scene without starting over; OpenAI describes multi-turn generation and editing as ways to progressively adjust an image while retaining context.
5. Poster with controlled typography
Create a vertical event poster with the exact headline ‘NIGHT MARKET’ and the exact subheading ‘FRIDAY • 7 PM • RIVERFRONT PLAZA.’ Show a lively illustrated evening market with paper lanterns, food stalls, and a blue river behind it. Use large cream lettering, strong contrast, generous margins, and no other words.
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Put required wording in quotation marks and say “exact.” Limiting the design to a headline and subheading reduces the chance of invented filler copy. Nevertheless, proofread every word, punctuation mark, date, and line break before using the poster publicly or commercially. For an important event, treat generated typography as a draft that may need manual correction.
6. Transparent-background product object
Create a single realistic ceramic teapot with a small sunflower pattern, shown in three-quarter view, centered, fully visible, isolated on a transparent background, no cast shadow, no extra objects, product-catalog lighting.
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This is a useful prompt for a catalog element, sticker concept, composite, or painting reference. It states that the teapot must be complete and centered, while removing common complications such as extra objects and a cast shadow. OpenAI’s original GPT-4o image-generation announcement specifically highlighted transparent backgrounds and precise color instructions as useful specifications.
Check the exported result’s actual transparency. A checkerboard-looking background in a preview is not necessarily the same thing as a file with a usable alpha channel.
7. Transform an uploaded street photograph
Use the uploaded street photograph as the structural reference. Preserve the building positions, road direction, and overall perspective, but transform the visual treatment into a hand-painted travel poster with limited colors: terracotta, cream, forest green, and black. Do not add people or change the architecture.
This is different from asking for a new street scene. It tells the model which properties belong to the source image and which property should change. OpenAI’s image-generation documentation describes image inputs, reference-image workflows, edits, and masked replacement.
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When uploading an image, be precise about whether you want to preserve identity, composition, architecture, object placement, or merely the general idea. “Make it artistic” gives the model too much freedom; “change only the visual treatment” gives it a narrower job.
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8. Isometric room design
Create an isometric cutaway illustration of a compact home studio for a ceramic artist. Include one workbench, a small kiln, two shelving units with labeled glaze jars, a window, a task lamp, and three potted plants. Use warm neutral colors, clean architectural linework, soft shadows, and a square composition. Keep every object separated and clearly visible.
Isometric scenes benefit from an inventory and spatial clarity. The object list prevents the room from becoming generic, while “separated and clearly visible” helps avoid objects merging into one another. If the labels on the glaze jars matter, generate the room first and add precise labels in an editing application rather than relying on tiny generated text.
9. Surreal editorial concept
Create a photorealistic editorial image of a giant transparent umbrella sheltering a tiny desert garden in the middle of a rainless city plaza. The umbrella should be the central object, with miniature cacti and one small lemon tree beneath it. Late-afternoon light, long shadows, muted concrete surroundings, wide cinematic frame.
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A surreal concept becomes easier to control when the impossible relationship is explicit: the umbrella shelters the garden, the plaza is rainless, and the garden contains particular plants. “Photorealistic” describes the treatment, while the unusual scale relationship supplies the creative idea.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.10. Repair and clean up an uploaded image
Use the uploaded image as the base. Remove the plastic bottle from the lower-left corner, reconstruct the missing section of the wooden table naturally, keep the person’s face and hands unchanged, preserve the original lighting and camera perspective, and do not alter any other objects.
This is a practical editing prompt rather than a style exercise. It defines the target area, the reconstruction task, and the protected areas. If the interface offers an editor or selection tool, select the bottle and a small surrounding region rather than the entire image. A smaller edit area can make the requested change easier to isolate, although results still require inspection.
Look closely at hands, faces, table edges, shadows, and repeated textures after the edit. If the system changes unrelated objects, ask for the same repair again with a more explicit instruction to preserve them, or use a masked edit if available.
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A reusable prompt template
Use this as a flexible starting point:
Create a [medium or visual format] of [main subject] [action or pose] in [setting]. Include [important objects and relationships]. Use [composition, viewpoint, lighting, color palette, and style]. The image should be [aspect ratio or orientation]. Include the exact text ‘[text]’ if needed. Avoid [specific unwanted elements]. If an image is attached, preserve [identity, structure, or object] and change only [requested edit].
You do not need to fill every bracket for every image. A simple sketch may need only a subject, action, and style. A poster or product composite benefits from more constraints. The goal is not maximum prompt length; it is unambiguous direction.
A practical refinement loop
- Generate a first draft. Start with the main subject and the most important visual constraints.
- Check the composition. Is the focal point prominent? Are objects in the correct positions? Is the subject fully visible?
- Check text separately. Proofread spelling, punctuation, capitalization, labels, and hierarchy.
- Change one problem at a time. Ask to move the camera, alter the palette, remove an object, or repair a region—but avoid changing everything at once.
- Protect successful details. Say what must remain unchanged, such as the face, clothing, architecture, lighting, or perspective.
- Finish outside the generator when appropriate. Manual retouching, typography, color correction, masking, and final resizing may still be the most reliable way to prepare an image.
What these prompts cannot guarantee
- Perfect first attempts: Clear prompts improve control but do not eliminate variation.
- Flawless typography: Always inspect generated words and numbers.
- Exact identity preservation: Reference images and consistency instructions can help, but important faces, products, and branded assets still need review.
- Automatic print readiness: Check dimensions, resolution, color, bleed, and text before ordering physical output.
- Identical behavior across products: ChatGPT Images 2.0, GPT Image 2, and other deployments may interpret the same prompt differently. Model names, limits, controls, and availability can also change.
Image systems also apply safety controls. A prompt or uploaded image may be blocked, refused, or modified when it conflicts with applicable policy; OpenAI documents moderation behavior in its image-generation API guidance.
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Frequently Asked Questions
Is GPT-4o still the current ChatGPT image model?
Not as a simple product label. OpenAI says GPT-4o was retired from ChatGPT on February 13, 2026, while ChatGPT Images remained a separate image-generation system. The current ChatGPT help documentation refers to ChatGPT Images 2.0, and OpenAI’s developer resources direct new API image-generation builds toward GPT Image 2.
Should I write one enormous prompt?
Usually not. Include the details that affect the result—subject, relationships, composition, style, text, and constraints—then refine the most important problem in a small follow-up. More words are not automatically more control.
Can these prompts generate readable posters and infographics?
They can help produce structured layouts and specified wording, but generated text still needs careful proofreading. For important or commercial designs, correct typography manually before publishing.
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Can I use a reference or uploaded image?
Image-input and editing workflows can use an uploaded image as a structural, identity, or style reference, depending on the product and model. State exactly what to preserve and what to change, and make sure you have the necessary rights to use the uploaded image.
The Bottom Line
The strongest image prompts are concrete rather than merely enthusiastic: name the subject, explain its relationships, set the composition, describe the visual treatment, specify exact text when needed, and protect important details during revisions. Try one prompt, inspect the result, and make a focused edit. Those principles remain useful even as the GPT-4o label gives way to newer ChatGPT and API image-generation systems.
Quick Recap
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