Flare vs Sunburst: Which One, and Why ChatGPT Won't Let You Choose

We serve both of these at the same price, so there is no side to take here and nothing to sell you by pointing at one. What there is: a distinction OpenAI's own documentation draws that almost every write-up has flattened, and seven pairs of frames OpenAI published itself.

Most people should start with Flare. It matches GPT Image 2 on picture quality, runs at roughly half the latency, and costs exactly the same per image as Sunburst. Sunburst is what you reach for when the quality ceiling matters more than the wait.

That is the whole answer. The rest of this page is why, and how to check it on your own work.

Flare vs Sunburst: what the documentation says each is for

The one sentence most write-ups get wrong

The launch announcement says Images 2.5 brings "sharper details", and almost everything written since has flattened that into 2.5 is better than 2. The developer documentation is more careful, and it says something different: Flare's quality is comparable to GPT Image 2, not better than it.

So "2.5 beats 2" is only true of Sunburst. Flare's real pitch isn't better pictures — it is the same pictures in half the time. What changed from GPT Image 2 goes through the rest of that generational question.

And the thing both models genuinely improved on is neither speed nor resolution. It is precise editing and subject preservation, which is the part no benchmark screenshot shows you.

They cost exactly the same. You're paying in time.

There is no premium tier here. Choosing Sunburst doesn't cost you more per image — it costs you more of your afternoon. These are OpenAI's published token rates, and the two columns are identical because the two models are billed identically.

Flare vs Sunburst on the same prompt, side by side

These are OpenAI's own paired runs from the GPT Image 2.5 prompting guide — same prompt, same size, one model each. We are citing them rather than re-running them, because a comparison between two models we sell is worth more when the vendor published it.

01Photorealism

same prompt  Create a photorealistic candid photograph of an elderly sailor standing on a small fishing boat. Weathered skin with visible wrinkles, pores and sun texture. Shot like a 35mm film photograph, medium close-up at eye level, using a 50mm lens.

flare · 1024×1536

sunburst · 1024×1536

02Exact text

same prompt  Give me an ad for a brand called Thread, a hip young street brand. The ad shows a group of friends hanging out together with the tagline "Yours to Create."

flare · 1024×1536

sunburst · 1024×1536

03A diagram with labels

same prompt  Create a detailed infographic of the functioning and flow of an automatic coffee machine. From bean basket, to grinding, to scale, water tank, boiler.

flare · 1024×1536

sunburst · 1024×1536

04A slide with figures

same prompt  A market opportunity slide with sample market sizing figures.

flare · 1536×864

sunburst · 1536×864

05A UI mockup

same prompt  Create a realistic mobile app UI mockup for a local farmers market. A simple header, a short list of vendors with small photos and categories, a "Today's specials" section, and location and hours.

flare · 1024×1536

sunburst · 1024×1536

06A four-panel comic

same prompt  Create a short vertical comic-style reel with 4 panels. Panel 1: the owner leaves through the front door, the pet framed in the window behind them. Panel 2: the door clicks shut, the pet turns toward the empty house…

flare · 1024×1536

sunburst · 1024×1536

07A classroom diagram

same prompt  Create a simple biology diagram titled "Cellular Respiration at a Glance" for high school students. Include glycolysis, the Krebs cycle and the electron transport chain, with arrows connecting the steps.

flare · 1536×1024

sunburst · 1536×1024

OpenAI's published pairs, from the GPT Image 2.5 prompting guide · cited, not ours

A "high" on Flare is not a "high" on Sunburst

OpenAI states this outright and it is easy to skim past: the same quality label does not imply the same image quality or response time across models. Three things follow from it, and the third one applies to the table above.

• Matching labels is not a controlled comparison. You cannot run Flare at high, run Sunburst at high, and conclude anything about the models — you have compared two settings that happen to share a name. The only comparison that means something is the same prompt at the same size, judged on the output.
• A higher tier is not reliably a better image. OpenAI's second warning, and the more expensive one to ignore: a higher setting doesn't guarantee a better result for every prompt. max costs about 16× what medium costs. It is not 16× better, and on plenty of prompts it isn't better at all.
• This applies to the pairs above too. They are there to show you what the difference looks like, not to score it. If you are making a real decision, run your own prompt through both — the first image is free and there is nothing to sign up for.

Why ChatGPT won't let you pick between Flare and Sunburst

If you have been hunting for this choice inside ChatGPT or Codex, you can stop. It isn't there. The built-in image tool doesn't expose the model, and it doesn't report which one ran either — two developers worked that out in public on r/codex the day it shipped.

That is the whole reason this site exists as a front end rather than an article. The choice you came looking for is a toggle on the generator — no code, no organization verification, no card. Open the generator, run the same prompt through both, and you will have your own answer instead of ours.

How to choose between Flare and Sunburst, in OpenAI's order

Notice what that path never asks: which one is worth the money. Neither costs more. The only currency in this decision is latency.

What independent testing found

Two sources, and they are here because neither of them is us. One is a developer who benchmarks every image model on release; the other is the public Arena leaderboard, with the caveat its own commenters put on it.

2.5 is the first model to genuinely improve on every test I throw at it… Flare medium seems to be the sweet spot and it's about 2x faster and 1/2 the cost of the old 2 medium.A developer who runs the same UI-generation task on every release · r/codex, launch week

We reached "Flare, medium" independently, which is worth saying out loud — two people measuring different things and arriving at the same default is a stronger signal than either of us asserting it alone.

On the Image Arena, Sunburst ranks first and Flare second across text-to-image, image edit and multi-image edit. Worth keeping in proportion, and a commenter on the announcement thread did that better than a press release would:

Going from 1,381 to 1,421 isn't 'destroying' the benchmark they previously set — it's an incremental gain.A commenter on the announcement thread

Model IDs, and three things that will trip you up

Migrating from gpt-image-2 changes exactly one thing in your request: the model string. Everything else stays valid. quality gained two tiers above high — xhigh and max — and the token rates did not move.

Pin the dated snapshot in anything whose output you have already reviewed and signed off. Then three things that are not in the migration note, and all three cost somebody an afternoon in the first week:

• Organization Verification is a hard gate. No verification, no GPT Image models at all. Start it first — it takes review time, and there is no way to shorten it once you are blocked on it.
• Complex prompts can take up to two minutes. Synchronous request handling will time out. This is not an error condition to retry through; it is the expected shape of a slow generation, so queue it.
• Rate-limit errors arrive inside an HTTP 200. A developer on the OpenAI forum lost an hour to it: "Spent a good hour thinking my code was broken before realizing the response body itself had the rate limit error buried inside a successful looking status code." Read error out of the body before you look at the status, not after.