GPT Image 2.5 Flare vs Sunburst: Which to Use?

Start with GPT Image 2.5 Flare when you are exploring compositions and styles. Try Sunburst when you have an established product or portrait image that needs careful revisions. These are starting points based on the models’ official positioning. Your inputs, acceptance criteria, and actual outputs should decide the final choice.

Both models generate and edit images. Flare can produce finished work, and Sunburst can generate from a text prompt. This guide covers choosing between the two after moving to Image 2.5. For the version decision, see our GPT Image 2 vs 2.5 comparison.

What separates Flare and Sunburst?

OpenAI positions Flare as the default for most applications, including social content, rapid prototyping, and high-volume generation. Sunburst targets visual workflows requiring tighter editing control and takes longer to generate. The official 50% latency reduction for Flare compares it with GPT Image 2. It does not establish a speed ratio against Sunburst or promise a particular HiAPI completion time. OpenAI launch announcement

A useful starting point is the stage of the image you are making.

This table recommends a testing order. It does not claim a measured quality winner for each task. Flare may complete a product edit in one attempt; Sunburst still requires inspection of details you did not ask to change.

For drafts, settle the direction first

An article cover usually starts with decisions about subject, composition, color, and space for a headline. Try one direction in Flare, check whether it fits the topic, then change one variable. Changing the subject, style, and camera angle together makes the useful adjustment harder to identify.

For a café event cover, you might hold the landscape composition, cream background, and headline space constant while exploring where to place the cup. Once the composition works, try a different background color. This gives you a clearer decision than a sequence of unrelated images.

Judge the output where it will appear. Reduce a cover to blog-card size and inspect whether the subject remains recognizable and the text area remains usable. More texture will not necessarily fix an unclear composition. If the result already works, continuing with Flare is a reasonable choice.

For edits, define what must stay

A product background replacement needs instructions about both the new background and the existing product. Specify whether proportions, packaging text, placement, camera angle, and lighting should stay fixed. An outfit edit needs equivalent requirements for facial features, expression, and pose.

Here is a product-editing prompt you can use with either model:

Change only the background to an even warm gray. Preserve the product’s outline, proportions, colors, label text, camera angle, and position. Keep the existing lighting direction and make the contact shadow blend naturally with the new background. Do not add text or decorations.

For an image close to delivery, try Sunburst and compare it with the input at full size. Correct background color is only one acceptance condition. Changed label lettering, an altered bottle opening, or drifting facial features can make an otherwise attractive result unusable. Save each round of a successive edit so you can return to an accepted version.

When comparing models, use the same input, prompt, quality, and dimensions. One pair of outputs can help you choose for that asset. It cannot establish a universal winner for product or portrait editing.

Separate quality settings from model choice

HiAPI currently gives both models the same request structure: text-only generation or editing with 1–16 reference images, plus six quality settings: low, medium, high, xhigh, max, and auto. Quality is a separate choice from the model. Comparing a low-quality Flare output with a high-quality Sunburst output changes two variables. Flare documentation · Sunburst documentation

As checked on September 9, 2026, the HiAPI model pages list identical prices for corresponding quality settings. Sunburst’s positioning does not imply a higher HiAPI price. Check live Flare pricing and live Sunburst pricing, then confirm actual charges in your task records.

For budgeting, consider cost per accepted image: total the actual charges for a batch and divide by the number of images that pass your checks. Track the time from submission to a usable result, including required retries and revisions. A cheaper or faster individual generation does not necessarily finish the batch sooner.

Make the decision with your own asset

Choose an image you actually need and write its acceptance criteria before generating. For example, the product label must remain intact, the background must become warm gray, and the result must work in a landscape placement. Check composition and the requested change, inspect preserved details at full size, then record actual cost and elapsed time.

Start with Flare while the direction is open. Try Sunburst when preserving specific details becomes the main difficulty. Both entries support generation and editing. Once a model meets your delivery requirements, keep the input, prompt, and settings as a reusable starting point for similar work.