OpenAI: GPT Image 2.5 Sunburst

GPT Image 2.5 Sunburst is OpenAI’s precision-oriented model for image generation and editing. It accepts text and image inputs and produces image outputs. Use it when a creative task depends on carefully modifying existing material, working with visual references or refining a composition through several steps. The brief can create a new scene, transform an existing image or guide an edit to a selected region. Sunburst and Flare are separate editions: Sunburst emphasises editing precision, while Flare is positioned for fast everyday generation.

For a new image, describe the subject, setting, composition, lighting and style, then state the intended shape and use. For a product concept, request a glass lamp on a stone surface with soft side lighting, a clearly visible silhouette and open space for a headline. For an edit, name the change and the elements that should remain recognisable: replace the background, adjust the light or alter a material while retaining the selected composition. The direct producer generation and edit workflows permit a prompt up to 32,000 characters and one to ten results.

Reference editing can use up to sixteen input images. Give each image a role so the instruction distinguishes the subject to retain, an environment to use and a style to apply. The model can also work with a mask that indicates an area to change. The source and mask need the same format and dimensions, and the mask must carry an alpha channel; the guide gives a size requirement below 50 MB. With several source images, the mask applies to the first. It guides the requested change rather than guaranteeing a hard boundary, so include preservation instructions in the brief and inspect the surrounding area in the result.

Quality settings are low, medium, high, xhigh, max and auto, with auto as the default. Low can support a quick visual draft, while higher settings are useful to compare when fine detail matters. Quality is separate from output dimensions and file compression. Standard sizes include 1024 × 1024, 1536 × 1024 and 1024 × 1536 pixels, and automatic or custom dimensions are also available. Choose the shape around the final layout before deciding how much detail the image needs.

Custom dimensions must be multiples of sixteen pixels, neither edge may exceed 3840 pixels, the aspect ratio must stay between 1:3 and 3:1, and total area must lie between 655,360 and 8,294,400 pixels. These conditions apply together. A 3840 × 2160 landscape fits the upper area limit, while a long edge by itself does not make an arbitrary pair of dimensions valid. Resolutions above 2560 × 1440 are described as experimental. Keep important objects, text and useful negative space within the intended crop instead of relying on more pixels to resolve the composition.

PNG is the default output format; JPEG and WebP are also supported. Compression from 0 to 100 can be selected for JPEG and WebP. Transparent, opaque and automatic backgrounds serve different layout needs. For transparency, choose PNG or WebP so the result can retain an alpha channel. A transparent asset can then be placed in another composition, while an opaque image supplies its own background. Keep the actual completed file together with the brief and selected output settings.

OpenAI documents direct generation and editing as well as a conversational image-generation tool that can retain prior results and apply follow-up instructions. In that conversational workflow, the action can be automatic, forced generation or forced editing when an image is in context. Use the chosen image as the starting point for the next change rather than silently switching to another variation. The documented streaming workflow can deliver up to three partial images before the final result; a partial preview helps show progress but is not the finished asset. The manufacturer interface also supports batch processing.

Check the edited subject, lettering, object placement and the boundary of a masked change at the intended display size. GPT Image can still struggle with precise text positioning, structured layouts or consistency across recurring subjects and brand elements. A focused next instruction should identify the visible issue and the elements to preserve. Sunburst is useful for a precise, reference-led creative workflow whose final artifact can be assessed against a concrete visual brief, with higher quality, dimensions and transparency chosen for that artifact.