ChatGPT Images 2.5: Faster, more precise, but not the

What happened

The models are meant to preserve subjects from reference photos better and follow editing instructions more reliably across multiple rounds. 0. For developers, OpenAI brings both models to the API. 5 Flare is the default pick for most uses, with higher image quality than GPT-Image-2 at 50 percent lower latency. 5 Sunburst, targets more demanding visual work with tighter control over edits, and it needs longer generation times to deliver.

Tests in ChatGPT's Chat mode, by contrast, always changed the rest of the image when we adjusted the banana color. Only in "6 Pro" mode did the image stay consistent in one run, but not in another. This may change over the course of the week as the rollout continues.

5 is also meant to handle complex visual instructions better, deliver more accurate content for real-world information, and work with transparent backgrounds and more demanding layouts. In our last article, for instance, we had ChatGPT turn the piece into an 80s magazine spread. It looked like this.

5 via Astra (Max) also produced a detailed magazine with a sample image based on our monkey-astronaut prompt, in a weaker and a stronger variant, without losing sight of the original instruction for worse quality. " For comparison, the results through plain ChatGPT Chat are also worth a look, but they show that the weaker model changes other details during translation too.

In one case, though, it nailed the current Microsoft CEO better. 5 / ChatGPT Chat (Medium and Instant) In ChatGPT, OpenAI is adding several new features alongside the new models. " It lets users draw directly in ChatGPT and use the sketch as a visual template for the finished image. You activate it with the "@Sketch" command, and OpenAI says it works well for diagrams, room layouts, or posters.

Why it matters

Both models use the same token rates. That's eight dollars per one million image input tokens and 30 dollars per one million output tokens. But since token use varies by model and quality tier, the same rates don't mean the same cost per image. 21 dollars with around 7,024 output tokens. 5 at the same price as the "high" tier of GPT-Image-2. 5 has no cheaper batch rate so far.

In early tests, though, Sunburst usually costs more per image than Flare despite identical token prices, probably because of longer reasoning runs. And unlike last time, OpenAI gives no average price-per-image figure. It's also unclear how OpenAI routes ChatGPT users between the two models. Neither the announcement nor the documentation says when ChatGPT reaches for the faster Flare or the more precise Sunburst.

In the API you can pick the model explicitly. The ChatGPT interface offers no such control yet. In our tests, the line currently seems to run mainly between Chat and Work. In Work, our prompts really do change only what's asked, no matter the reasoning settings. These targeted edits are the focus of the model improvements.

In Chat, though, more details keep shifting in the follow-up images, even with reasoning set to high. Only at the "6 Pro" setting does the stronger model sometimes appear to kick in. As noted, the new model's focus is editing. It's meant to change only the requested elements and leave the rest of an image untouched, even with more complex subjects and backgrounds.

In longer conversations, earlier changes should stay consistent without image quality dropping over multiple editing steps. OpenAI shows this with a room redesign, for example. Where the older model changed other details with every edit, the new model stays stable even across several iterations. A quick test through ChatGPT Work with GPT-6 Astra (Max) shows how well this works.

We used the following prompt and then iteratively adjusted one small detail (banana color) and one large one (the big cat). 5 / Astra (Max) On a side note, this is probably the best version of a horse riding an astronaut that an OpenAI image model has produced in our tests. 0 (Thinking variant).

What to watch

Templates are ready-made prompts meant to make it easier to get started with formats like posters, logos, infographics, thumbnails, illustrations, or ads. They give you a structure instead of a blank canvas and pin down your requirements through targeted follow-up questions. Users can also place comments directly on images and share the prompts they used, so others can try the same idea with their own photos and details.

As an example, OpenAI points to a currently viral prompt that generates portraits in 1980s style. In Arena's text-to-image leaderboard, the new models hold the top two spots for now.