GPT Image 2.5 is OpenAI’s image-generation and editing family released on September 8, 2026. The API family includes GPT Image 2.5 Flare for fast, high-quality everyday generation and GPT Image 2.5 Sunburst for more precise, detail-led creative and editing work. Both accept text and image inputs and produce images. The family emphasizes sharper detail, more natural lighting and texture, stronger preservation of reference subjects, precise local edits, and better consistency across repeated revisions.

Flare is the default choice for most applications and is optimized for fast, high-quality generation. Sunburst is positioned for premium workflows where tighter control and editing precision are more important, and it takes longer to generate. Choose Flare for broad ideation, creator content, prototypes, or higher-volume work. Choose Sunburst when an approved subject, product, layout, or campaign asset must survive detailed changes with fewer unintended edits.

Not currently. The model selector inside the embedded Wan 3.0 workspace shows the actual registered model, which is GPT Image 2 at the time this page was prepared. The page explains GPT Image 2.5 and helps you prepare stronger briefs, but it does not relabel GPT Image 2 or claim that a 2.5 API request is being sent. A separate backend integration and validation task is required before this site can offer the new models.

Yes. The model family accepts image references and is designed for targeted editing. State exactly what should change, then state what must remain recognizable or unchanged. For a product background edit, protect geometry, viewing angle, material, label area, reflections, and contact shadow. For a portrait edit, protect facial identity, hair, expression, pose, crop, and light direction. Review the unchanged regions as carefully as the new region.

Use a four-part structure: source role, change request, preservation rules, and output context. For example: use image one as the identity source; replace the office with a quiet evening studio; preserve the person’s face, hair, expression, pose, camera angle, and navy jacket; deliver a landscape editorial image with space for a headline. Keep the first change modest, compare it with the source, and add another change only after the important details remain stable.

Yes. OpenAI describes improved consistency across multiple edits, with earlier decisions more likely to remain stable as a person continues refining the image. A disciplined workflow still matters: save the last approved result, repeat the protected details, change one variable, and record the prompt. If several unwanted changes accumulate, restart from the last accepted image rather than asking the model to repair a long chain of drift.

The model family supports complex layouts that include transparent backgrounds, and the API model documentation includes background controls. Transparency should still be reviewed like any production asset. Zoom into hair, glass, fabric fibers, soft shadows, and semi-transparent edges; check for halos or color contamination; and test the exported image over both light and dark backgrounds before delivery. Availability of a specific control depends on the product or API integration you are using.

No. OpenAI reports generation latency reduced by up to 50% compared with Images 2.0, and separately describes Flare as its fastest model for high-quality everyday image generation. “Up to” is a maximum comparison, not a promise for every prompt, quality setting, image size, service load, or application. Measure the workflow that matters to your team, including queue time, revision count, download, review, and any post-production.

Start with Flare when you need many strong directions quickly and the image will go through normal selection and design finishing. Test Sunburst when exact product geometry, local edits, or preservation across several revisions is the central risk. In both cases, use an authorized source, list the protected product details, request one channel-specific composition at a time, and inspect the full-resolution result before a campaign asset is approved.

No. Better instruction following and layout understanding do not replace verification. Check every character, number, unit, label, relationship, and factual claim against the approved source. For prices, legal statements, safety information, data visualizations, or accessible copy, use the generated image as a visual draft and rebuild critical content in an editable design layer. That keeps spelling, semantics, contrast, reading order, and later localization under direct control.

GPT Image 2.5 adds documented improvements in detail, natural lighting and texture, reference-subject preservation, targeted edits, multi-turn consistency, complex layouts, and generation speed. The API also introduces two explicit choices: Flare for fast everyday quality and Sunburst for greater precision with longer generation time. Existing GPT Image 2 workflows may still be useful; migration should be based on tested gains for your prompts, costs, review criteria, and delivery needs.

Keep the authorized source files, model and variant name, exact prompt, relevant settings, output version, edit history, reviewer, approval date, and intended channel. Note which details were protected and which were changed. Preserve applicable provenance metadata and document any post-production typography or retouching. A compact record makes the result reproducible, supports rights review, and helps a team understand why one version was selected over another attractive alternative.