GPT Image 2.5 Flare vs Sunburst: which one should you use?

Use GPT Image 2.5 Flare by default and switch to Sunburst when an edit has to be precise. Flare is OpenAI's default choice for most applications and returns images quickly. Sunburst is the more capable model: it holds tighter control across edits and takes longer to render. Both read exactly the same request fields, so moving a job from one to the other is a one-word change to model.

That short answer covers most decisions. The rest of this guide explains where the difference shows up, what each option costs on SeedRouter, and how to test the choice on your own images instead of trusting a general rule.

What is the difference between Flare and Sunburst?

OpenAI released GPT Image 2.5 on September 8, 2026 as two models rather than one. They share an API contract and differ in how much work they put into each image.

The table is deliberately short. Neither model adds a parameter the other lacks, and neither is limited to a smaller canvas. The practical difference is the trade between waiting time and how faithfully the result keeps what you asked it to keep.

When should you pick Flare?

Pick Flare when you will look at many images and keep a few. Social variants, concept exploration, thumbnails, and first drafts of a layout all fit here. If a request asks for ten images and you plan to choose one, the faster model shortens the whole loop.

Flare is also the sensible starting point for a new prompt. Write the prompt, run it on Flare at low or medium, and fix composition problems while each attempt is quick. Moving to Sunburst before the prompt is settled mostly makes each failed attempt take longer.

When is Sunburst worth the wait?

Sunburst earns its time on edits. When you send reference images with images, or a mask that marks one region to change, the job is usually "change this, keep everything else." That is the case where tighter control across edits matters: a product color change that must not move the label, or a background swap that must leave the subject untouched.

It is also the better candidate for a final asset after the prompt is fixed. Run the settled prompt on Sunburst at a higher quality step and compare it with the Flare version side by side. If you cannot see a difference in the parts of the image your audience will look at, keep Flare.

Do Flare and Sunburst cost different amounts?

On SeedRouter, no. Every model ID in a channel has the same price, so Flare and Sunburst cost the same within a channel. What changes the bill is the channel you choose, not the tier.

• Standard IDs (gpt-image-2.5-flare, gpt-image-2.5-sunburst) charge one flat price per delivered image at any size or quality.
• Official IDs (gpt-image-2.5-flare-official, gpt-image-2.5-sunburst-official) bill the tokens each render reports, so quality and size change the cost.

These are the current rates, read live from the same table that bills your account:

A flat price makes high, xhigh and max cost the same as low on the Standard channel. On the Official channel the higher steps spend more output tokens, which is why the table above shows each quality separately.

What changed from GPT Image 2?

Three things matter for an integration. First, GPT Image 2.5 adds two quality steps, xhigh and max, above high, where GPT Image 2 stops. Second, it is two models instead of one, which is the choice this guide is about. Third, the request shape stayed the same: the same endpoint, the same field names, URL inputs for references and masks, and the same asynchronous task flow.

That last point makes an upgrade cheap to try. Keep your GPT Image 2 request, change model to gpt-image-2.5-flare, and compare the output. The GPT Image 2.5 reference lists every field and constraint if you want to use the new quality steps.

How do you test the choice on your own images?

A general rule is a starting point, not a verdict. Run a small comparison with the prompt you actually ship:

1. Pick three briefs: a plain generation, a reference edit, and the hardest image you expect to make.
2. Submit each to Flare and Sunburst with the same size, quality and prompt.
3. Look only at what your use case cares about, such as a label, a face, or the edge of a product.
4. Note the waiting time for each task alongside the image.

If Sunburst only wins on the edit brief, route edits to Sunburst and everything else to Flare. Because the fields are identical, that routing is a single condition in your code.

Frequently asked questions

Can I switch between Flare and Sunburst without changing my request?

Yes. Change the model field and nothing else. Both models accept the same prompt, size, quality, background, output format, image count, references and mask.

Which model should I use for transparent backgrounds?

Either one. Set background to transparent and output_format to png. Transparency is a request setting, not a feature of one tier.

Is Sunburst always better quality?

It is the more capable model, but "better" depends on the job. On quick drafts you may not see a difference that justifies the extra time. Compare both on your own briefs before deciding.

Start with Flare, prove the case for Sunburst

Default to Flare, keep the prompt settled on it, and move a job to Sunburst only when a side-by-side comparison shows the difference your users will notice. Try both in the GPT Image 2.5 Playground, and see OpenAI's GPT Image 2.5 announcement for the vendor's own description of the two models.