GPT Image 2.5 review: Sunburst vs Flare for creative work

GPT Image 2.5 gives creative teams two choices: Sunburst, which OpenAI positions around image quality, and Flare, which it positions around speed. Both generate and edit images. The useful question is which one meets the requirements of the image you actually need. OpenAI model guidance.

Our editorial recommendation: evaluate Sunburst for a demanding final asset and Flare for exploring directions. Keep the brief consistent so that you can judge the model choice. This is a starting hypothesis for your project, not a claim that one variant wins every task.

This GPT Image 2.5 review covers the documented capabilities and Quickmake’s integration as of October 5, 2026. We have not run a scored hands-on benchmark for this article, so there are no invented speed measurements, output ratings, or before-and-after results. The prompts below are original briefs you can try.

For Sunburst and Flare credit estimates and a prepared prompt, visit the GPT Image 2.5 guide. The GPT Image family page compares generations and release dates. For the broader workflow, start with the AI image generator.

GPT Image 2.5 Sunburst vs Flare

OpenAI describes Flare’s image quality as comparable to GPT Image 2 and Sunburst’s as higher. It also describes improvements in precise editing and subject preservation for both 2.5 variants. These are provider claims, not our measured results. OpenAI’s GPT Image 2.5 overview.

For a small campaign, choose a representative brief before evaluating either model. A beautiful landscape tells you little about whether the model can deliver the product scene your campaign requires. Judge the result at the size where your audience will see it, as well as at full resolution.

Where GPT Image 2.5 fits in a design workflow

We would evaluate it at the point where a written brief needs to become an image: a product setting, editorial illustration, campaign background, or reference-based variation. Quickmake supports Sunburst and Flare alongside GPT Image 2, so you can keep the resulting assets in the same creative workspace.

For a campaign layout, ask for the image layer first. Reserve space for the headline and build the copy separately in the design editor. That makes later changes to a price, date, or call to action much easier than regenerating the entire composition.

The model can help you explore the visual direction. Your layout still needs hierarchy, readable copy, and a clear focal point. Treat those as separate review decisions.

GPT Image 2.5 image editing: what to check

Both model variants accept image input and produce image output. That makes reference-based editing part of the family’s documented capabilities. Sunburst model documentation, Flare model documentation.

In Quickmake, choose the model and attach the reference through the generator’s image controls. A useful first task is a single change with a clear acceptance criterion: move a product into a new setting while retaining its recognizable shape.

For example, compare the cap, label, and silhouette of a bottle with the source image. If those details are wrong, a convincing background does not make the result suitable for your product page. Use the AI image editing workflow to develop the asset, then approve the complete result before placing it in a campaign.

For repeated edits, retain your approved source alongside the variations. This gives you a clear reference when deciding whether the latest direction still represents the product accurately.

Three GPT Image 2.5 prompts to start with

These briefs demonstrate different creative jobs. They are suggestions, not samples of verified model output. Adapt the subject and visual constraints to your project.

1. A product campaign background

Create a landscape product photograph of a cobalt-blue insulated bottle on a weathered picnic table beside a misty lake. Early morning light, subtle condensation, bottle on the right third. Keep the left side visually quiet for a headline. No text or logos.

The decision here is composition. Can the image support a headline without covering the subject? Test it inside your intended layout before spending time on smaller details. The GPT Image 2.5 prompt starter includes a product-scene brief to adapt.

2. A tactile editorial illustration

Create a square illustration of a small sailboat crossing a peach-colored sea, made from layered cut paper. Navy sail, ivory sky, three simple clouds, soft tactile shadows. Keep the boat silhouette clear at small sizes. No lettering.

This brief is useful for evaluating a graphic direction. Put the image into a small social preview: if the boat disappears into the texture, revise the scale or simplify the scene.

3. A controlled product edit

Use the attached product photograph. Replace the surrounding scene with a warm cream studio backdrop and a pale stone surface. Keep the bottle shape, cap, label wording, and camera angle consistent with the reference. Add a soft contact shadow. Do not add props.

Attach your own product reference before trying this edit. The important question is whether the result could represent that specific product, not simply whether it looks like an attractive bottle.

GPT Image 2.5 pricing in Quickmake

Quickmake quotes generation in AI credits. The GPT Image models and credits section reads its estimates from the same model configuration as the product. The table shows a default square image; review the generator’s quote for your actual settings and references before submitting.

An OpenAI API price is a different unit of comparison from a Quickmake credit estimate. For direct API usage, consult the pricing tables on the Sunburst and Flare model pages. For account allowances, use Quickmake pricing.

For your own project, keep a simple record of credits spent and assets accepted. If five attempts produce one usable image, the single-attempt quote only describes part of the effort. Revision time also matters when choosing between models.

GPT Image 2.5 vs GPT Image 2

If you already have a GPT Image 2 workflow that works, preserve a few representative briefs and their approved results. Compare the new variants against those requirements before changing your default.

Use a short scorecard: usable composition, accurate subject, acceptable detail, revisions required, and credits spent. Decide which criteria are essential before seeing the new images. This makes it harder for an impressive but unsuitable result to distract from the job.

A new model name alone is not a reason to redo finished creative work. Evaluate it on the next brief where the result, workflow, or turnaround could improve.

Alternatives: Nano Banana, FLUX, Grok Imagine, and Seedream

Quickmake supports several image-model families. These are alternatives to evaluate, not a ranked leaderboard from this review:

• Nano Banana: compare Nano Banana 2 and Pro on your generation or reference-editing brief.
• FLUX: choose a specific FLUX version and check whether it supports the workflow you need.
• Grok Imagine: evaluate Grok Imagine 2.0 on the same subject and composition.
• Seedream: compare Seedream 5 Lite and Flash using the available settings and credit estimates.

The AI models hub connects these family pages. Start with one real task and compare two plausible candidates; a project rarely needs an exhaustive contest before you can make progress.

Is GPT Image 2.5 worth trying?

Yes, if you have a concrete generation or editing task and want to evaluate the two variants within your existing workflow. Our starting recommendation is Sunburst for demanding visual requirements and Flare for exploring directions, followed by a comparison using your own acceptance criteria.

Open the GPT Image generator options, choose a model, and prepare your brief. Quickmake requires sign-in and sufficient credits to generate. You review the request before submitting it, then bring the selected image onto the canvas to finish the design.