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GPT Image 2.5 Sunburst Image to Image
GPT Image 2.5 Sunburst Image to Image
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Support all image formats and support multiple selection
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Reference-based generation with clear priorities
GPT Image 2.5 Sunburst image to image is useful when a new visual needs to retain important information from existing pictures. You might have a product photograph, an approved campaign layout and a material reference. Rather than blending them indiscriminately, tell the model how those sources should work together.
A good image transformation brief establishes priorities. If the product shape is essential but the room is only inspiration, say so. If a layout reference controls placement but not colors, make that distinction explicit. Reference-based generation is easier to evaluate when you know which source should be responsible for each part of the result.
This page accepts up to 16 pictures and returns one new image per request. GPT Image 2.5 Sunburst is aimed at detailed creative and editing workflows, but references do not guarantee perfect reproduction. Compare identity, geometry, labels and scale with the originals before approving the output.
Prepare a GPT Image 2.5 image to image brief
Decide which details must survive the transformation before uploading additional references.
Choose a primary reference
Start image to image with the picture that best defines the subject. Add another view only if it reveals a needed feature. Keep a separate reference for the setting or style. A collection of inconsistent product versions makes the intended design harder to identify.
Assign a role and a priority to each input
Tell GPT Image 2.5 Sunburst: “Use the bottle shape and label from the first image. Use the second image for the room and light. Keep the bottle upright and centered.” This gives reference-based generation a practical hierarchy instead of an open-ended blending request.
Inspect the result by source
After selecting settings and generating, compare each important area with the relevant reference. Check the product against the product image, then the layout against the composition reference. This is more reliable than accepting an image transformation because the overall color palette looks familiar.
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Detailed image to image workflows
Use reference pictures to communicate the parts of a brief that words struggle to describe.
Product campaigns with recognizable packaging
Use image to image to explore a new setting around an existing product. Ask for the cap, silhouette and label placement to remain consistent. Check the generated package at full size, particularly if the camera angle reveals surfaces absent from the reference.
Character scenes with an appearance checklist
For GPT Image 2.5 character work, define the visible traits that matter: hairstyle, face shape, clothing and accessories. Keep source pictures consistent and change the scene deliberately. A similar mood is not the same as a consistent identity.
A new variation of an approved composition
Reference-based generation can use a layout picture to guide spacing while a second input supplies the subject. Describe where creative freedom is allowed. If every position must be exact, finish the layout manually rather than expecting a generated image to behave like an editable template.
GPT Image 2.5 Sunburst image to image questions
How is Sunburst image to image different from text to image?
Image to image uses at least one uploaded picture alongside your brief. That picture supplies visual information such as a product design or character appearance. Text to image starts from words alone, making it better suited to a new composition without a specific visual source.
How many references does GPT Image 2.5 Sunburst support?
You can upload up to 16 pictures on this page. Each image to image request produces one output. Use only the references needed to explain the task, and identify their roles in the prompt when they show different subjects or styles.
Can I preserve a logo or label exactly?
You can ask GPT Image 2.5 Sunburst to retain those details, but exact reproduction is not guaranteed. Inspect letters, spacing and proportions. If a brand asset must be identical, place the approved logo or final label onto the finished composition using a design editor.
Can Sunburst keep the same person across new scenes?
Reference-based generation can guide appearance, especially when the source images agree with each other. Still compare facial features, hair and clothing after each request. Large changes in pose, lighting or viewpoint can make differences harder to notice at first glance.
How do I combine a product photo and a background photo?
Name their roles directly in the image to image prompt, then specify scale, camera angle and contact with the surface. Check that the product has not inherited unrelated details from the background reference and that the lighting makes sense across the whole composition.
What does GPT Image 2.5 Sunburst image to image cost?
The output tiers are 1K for 1 credit, 2K for 2 credits and 4K for 3 credits. The panel shows the selected charge before submission. Each new image transformation is a separate generation, even when it reuses the same references.
Is there a slider to lock how closely the source is followed?
This image to image page has no reference-strength or denoise slider. Use the written brief to distinguish protected features from areas open to change. For a smaller revision to one image, use the Sunburst image editor instead of combining several references.
Give your references an order of importance
Use GPT Image 2.5 Sunburst with a clear subject reference and a focused transformation brief. Check the details that define the subject before approving the scene.
