Try transparent product cutouts, multi-image compositions, infographics and reference-guided edits with GPT-Image-1.5.
Compare the examples with your own requirements. Review small text, product edges and geometry before using a result.
Open image-to-image workflowExample tasks
Explore the original examples and their prompt directions. Results vary with your inputs and settings.
Generated with GPT-Image-1.5
Virtual try-on
This is aimed at fashion and ecommerce teams that want to reuse approved model photography while swapping in new garments without booking another shoot.
Keep the original background, framing, face, and pose. Apply the uploaded yellow floral dress naturally to the model with believable draping and lighting.
Transparent PNG
Compare the lifestyle source with the product cutout. Check the edges and label before using it in a catalog.
Extract the skincare bottle onto a transparent RGBA background with crisp edges, preserved label legibility, and a polished product finish.
Infographic
This is the kind of output consultants, marketers, and in-house design teams pay for when they need readable, presentation-ready diagrams instead of generative art.
Build a modern navy presentation slide explaining the coffee roasting process with four exact stage labels and clean visual hierarchy.
Product UI
This is where interface hierarchy matters: spacing, cards, typography, and believable app structure instead of fuzzy concept art.
Create a polished personal finance dashboard inside a bezel-less smartphone with a donut chart and three exact merchant rows.
Sketch to render
The A-frame cabin sketch guides this render. Compare the geometry and opening positions against the source.
Turn an uploaded A-frame cabin sketch into a photoreal render while preserving the exact layout, perspective, and opening positions.
Where it may help
GPT-Image-1.5 works best when the workflow has structure: a reference image, a layout to follow, or a specific production constraint like transparent output. These are the narrower cases where it makes sense to test.
Try it when the real need is transparent output, clean cutouts, and product-prep steps that are awkward to do manually at scale.
Useful when you want to test whether a garment-application workflow can work with your existing model photography and product references.
Worth testing when you need structured visual communication with readable labels and a more presentation-like layout.
Still relevant for users who want to explore interface-like outputs and see how far the model gets on hierarchy and in-image text.
A reasonable test case when the output starts from a sketch, layout, or structured input and the model needs to keep that structure recognizable.
Some users simply want GPT-Image-1.5 available as an option. This page exists to support that choice clearly and honestly.
These tasks need extra testing before you choose a model.
Compare a few of your common tasks with Nano Banana 2 and GPT Image 2 before deciding.
Run a small trial and compare output quality, time and credit use before choosing a model for a larger set.
Test open-ended scenes with several models when you do not have a sketch, reference or layout to guide the result.
What to expect
Test with your own product images, layout requirements and output settings.
The examples cover transparent backgrounds, layouts and multiple references. Use them to choose a task to try.
Useful when
You want to test background removal, clean product isolation, or other catalog-style tasks where transparent output is part of the workflow.
Watch for
The result still has to earn its place through output quality; capability alone is not enough.
Useful when
You want to test infographics, dashboard-style mockups, or other images where hierarchy and readable text matter more than pure aesthetics.
Watch for
Output consistency can vary, so test with your actual inputs before committing to a production workflow.
Useful when
You want to test compositing or virtual try-on scenarios that depend on multiple inputs rather than one prompt-only image.
Watch for
Support for the workflow does not automatically make it the best model choice overall.
Why it may still be worth testing
Review the result for the placement where you plan to use it.
Transparent backgrounds and compositing can reduce manual steps. The final result still needs review.
Transparent PNG output can remove a whole background-removal step from catalog prep and merchandising workflows.
Structured infographics and UI mockups reduce the need to move every early deliverable into Figma or Photoshop before it becomes readable.
Virtual try-on and multi-image compositing let teams squeeze more value out of existing model and product photography instead of reshooting every variation.
Compare the geometry, labels and visual hierarchy with your source material before approving a result.
Use lower quality for faster iteration and higher quality when the final asset needs to hold up in production or client review.
Compare model results, explore a feature, or find a starting point for your next project.
Feature
Start from a reference image and transform it into edits, restyles, cleanups, and new visual directions.
Open pageFeature
Describe an idea and generate images for campaigns, product concepts and creative projects.
Open pageFeature
Launch prompt variations, ratios, and reference sets in one batch so your team reviews the full output set together.
Open pageUse case
Turn a phone-shot or rough source image into a studio-quality ecommerce product photo without changing the product itself.
Open pageUse case
Keep the product and packaging locked while replacing distracting backgrounds with cleaner catalog or lifestyle scenes.
Open pagePrompt starters
These prompts lean toward production deliverables instead of generic visual exploration, because that is where GPT-Image-1.5 should earn its keep.
Goal: Virtual clothing try-on for a fashion ecommerce product page. Background and scene: keep the original model photo exactly the same. Subject: the woman from the source image now wearing the uploaded yellow floral dress. Key details: match drape, folds, lighting, and body geometry naturally. Constraints: preserve her exact face, pose, hairstyle, and proportions.
Try this promptGoal: Prepare a product cutout for catalog use. Background and scene: transparent RGBA PNG. Subject: the skincare bottle from the uploaded image. Key details: crisp silhouette, preserved label readability, clean edges, subtle contact shadow. Constraints: keep the product geometry exact and do not restyle the bottle.
Try this promptGoal: Create a polished educational infographic. Background and scene: deep navy presentation slide. Subject: the coffee roasting process. Key details: clear stage flow, minimalist icons, and the exact labels Green Beans, Drying Phase, First Crack, and Cooling. Constraints: keep typography clean, legible, and completely free of gibberish.
Try this promptGoal: Create a realistic mobile app UI mockup. Background and scene: soft gray presentation background with a modern smartphone frame. Subject: a personal finance dashboard. Key details: donut chart, white interface, and transaction rows for Whole Foods, Uber, and Starbucks. Constraints: make it feel like a real shipped iOS app, not concept art.
Try this promptGoal: Turn an architectural sketch into a photoreal render. Background and scene: golden-hour pine forest setting. Subject: the A-frame cabin from the uploaded sketch. Key details: charred timber siding, reflective glass, matte black standing-seam roof. Constraints: preserve the exact layout, perspective, and structural openings from the sketch.
Try this promptYour next image
Start with a product cutout, a composition or a layout you need to create.
