GPT Image 2.5

What GPT Image 2.5 is good at

GPT Image 2.5 keeps everything that made GPT Image 2 the "use the output as-is" model — legible typography, world-knowledge grounding, prompts that are actually followed — and pushes on the one axis its predecessor left on the table: resolved detail. Fabric weave, hair, small text on a distant sign, the edge where a product meets its reflection — the places where earlier renders went soft now hold up when you zoom in. OpenAI describes the release as sharper detail, stronger style adherence and more control over edits, and that matches what we see on ZOOOP.

The release comes as two versions of one model. Flare is the fast default: it delivers higher quality than GPT Image 2 at noticeably lower latency, so it is the right pick for everyday generation and high-volume iteration. Sunburst trades speed for precision — it is built for premium visual workflows where control over each edit matters, such as production-ready campaign creative or polished product imagery. On ZOOOP they sit side by side as the Flare and Sunburst versions, with identical parameters; switching is one click.

Quality tiers that go further

GPT Image 2 offered Low, Medium and High. GPT Image 2.5 adds XHigh and Max above them, and the ladder is worth understanding rather than just cranking to the top. Low and Medium cover drafts, social posts and most editorial frames. High handles dense multi-element compositions. XHigh and Max exist for the case where the image is the deliverable — a printed key visual, a hero image viewed on a large screen, a 4K background plate — and fine texture must survive scrutiny. The higher tiers take longer and cost more; the right workflow is to explore on Low, lock the composition, then promote the single keeper to the tier the final use demands.

4K and up to 16 references

Output now reaches 3840×2160 (and 2160×3840 for vertical screens) for the widescreen and tall ratios — 21:9, 16:9, 9:16 and 9:21. Every other aspect ratio tops out at 3k, which still exceeds 2560 pixels on the long side. ZOOOP disables the 4K combinations the model does not accept, so a request that would be rejected upstream never gets submitted or charged.

On the input side, the reference-image slot takes up to 16 images (GPT Image 2 stopped at 10). That matters for product composites and layout work: packshots, props, a colour reference and a rough layout frame can all go in together, and the prompt describes how they combine. The edit pass preserves what you reference and applies only the change you describe.

Where it is weaker

The trade-off is at the top of the ladder: Max is the slowest and most expensive tier, and for many scenes the visible difference from High is small. If you find yourself defaulting to Max, step back down and check whether the detail you were chasing is really there. Sunburst likewise adds latency — reserve it for edits where control is the point.

For pure photoreal portraiture with exact skin tone and colour, Flux 2 Pro still edges it. For vector or SVG deliverables, Recraft V4.1 is the right tool. For dense multilingual text and fact-heavy infographics, Nano Banana Pro remains the safer pick. And if the brief is fast batch drafts where each frame is disposable, Flux 2 Flash turns them around quicker.

A reasonable mental model

Default to GPT Image 2.5 Flare on Low or Medium for anything with on-image text, real-world objects, or a multi-part instruction — that is the widest coverage on the platform for a "ship the first render" workflow. Move to High, XHigh or Max only when the output is the final asset and will be viewed large. Switch to Sunburst when you are editing an existing image and the edit has to land exactly where you point. Reach for GPT Image 2 only if you need to match renders from an existing project; for new work, 2.5 supersedes it.