ChatGPT Images 2.5: Editing, Sketch, and API Models
ChatGPT Images 2.5 adds more faithful reference editing, stronger multi-turn consistency, Sketch, Templates, and Flare and Sunburst API models.
Before reading, try the current ChatGPT Image model.
Developer: OpenAI · Released: September 8, 2026 · ChatGPT product: ChatGPT Images 2.5 · API models: GPT-Image-2.5 Flare and GPT-Image-2.5 Sunburst
This version page covers the changes introduced with ChatGPT Images 2.5. For the model family's history and architecture, see the ChatGPT Image generation guide. For the preceding release's Reasoning Mode and baseline capabilities, see ChatGPT Image 2.
ChatGPT Images 2.5 is an incremental release focused on the part of image generation that happens after the first prompt: keeping a reference subject recognizable, changing only the requested element, and carrying earlier edits forward without gradual quality loss. OpenAI also added product tools that make the process feel more like a design workflow, including a drawable reference canvas, starting templates, comments on an image, and shareable prompts.
OpenAI says people create more than 3 billion images each week across ChatGPT Images and the GPT Image models in the API. That figure is a statement about aggregate product usage, not a benchmark for model quality. The release announcement is the primary source for the capabilities and availability described on this page.
What Changed From Images 2.0?
| Area | Images 2.0 | Images 2.5 | Why it matters |
|---|---|---|---|
| Reference fidelity | Reference-led generation and editing | Better preservation of recognizable subjects, lighting, and texture | Variations can stay anchored to a source photo |
| Editing precision | Conversational edits with the existing image context | Better isolation of the requested product, background, or copy change | A small revision is less likely to disturb the rest of the asset |
| Multi-turn consistency | Iterative editing in ChatGPT | Earlier edits are more likely to persist through longer conversations | Campaign and design revisions require fewer resets |
| Instruction handling | Complex prompts and visual reasoning | Stronger handling of complex information, layouts, transparent backgrounds, and style direction | Detailed briefs are more dependable |
| Generation latency | Images 2.0 baseline | Up to 50% lower latency, according to OpenAI | Faster iteration and higher-throughput workflows |
| Creative controls | Prompt and image input | Sketch, Templates, image comments, and prompt sharing in ChatGPT | More ways to express intent than text alone |
Source: OpenAI's ChatGPT Images 2.5 announcement. The comparison describes the release delta; OpenAI does not publish a universal quality score for each row.
The important distinction is workflow reliability rather than a new architecture claim. OpenAI presents Images 2.5 as a model that is better at preserving what is already correct while applying a targeted change. That is especially relevant for product imagery, portraits, marketing variants, infographics, and other assets that go through several rounds of review.
Reference Fidelity and Precision Editing
Images 2.5 is designed to keep the identity and visual treatment of a reference while changing the setting, style, clothing, or composition. OpenAI specifically describes more recognizable subjects, more natural lighting and richer textures, and better retention of distinctive features. For an API workflow, this means a set of variants can remain tied to the same source image instead of drifting from one generation to the next.
Precision editing is the companion improvement. A user can ask to update one element, such as a product, background, or piece of copy, while preserving the subject, composition, and brand treatment around it. The useful test is not whether the model can make a new image; it is whether the requested change is local enough that the approved parts of an image remain approved.
This is an OpenAI capability claim, not a guarantee that every edit will be perfectly isolated. Small details should still be checked before publication, particularly faces, dense typography, logos, and images with overlapping objects.
Multi-Turn Editing Consistency
Long editing conversations create a different failure mode from one-shot generation: each revision can slowly alter earlier decisions. OpenAI says Images 2.5 follows specific editing instructions more reliably over multiple turns, keeps earlier changes consistent, and builds on the existing result without degrading image quality as quickly.
The practical workflow is straightforward:
- Generate a base image from text and references.
- Request a focused revision, such as a background, product color, or label change.
- Add another correction without re-uploading or rebuilding the whole brief.
- Review the final asset against the original reference and brand requirements.
The model's improvement reduces regeneration, but it does not remove the need for an approval checkpoint. Keep the original prompt, references, and final comparison in the production record when the image is used commercially.
Sketch, Templates, Comments, and Prompt Sharing
Sketch as a Visual Reference
Sketch lets users draw directly in ChatGPT and use that drawing as a guide for the final image. A rough room plan, an outfit contour, or a simple doodle can communicate spatial relationships that are difficult to describe in prose. The workflow is to draw, add a description of the desired style and details, and invoke Sketch with @Sketch.
Sketch is a product feature layered around the image model, not a separate API model. OpenAI's announcement demonstrates it for still-image creation. Early media tests also explored animated outputs, but that is an independent observation rather than an official API capability or guarantee.
Templates for Common Formats
Templates provide a starting point for common creative formats such as Poster and Merch. They move the user from a blank prompt to a format with an implied layout, after which the user can specify the information, design elements, and visual style. This is useful when the problem is not image generation itself but expressing a familiar deliverable clearly.
Comments and Shareable Prompts
Users can place comments directly on an image to identify the area that needs revision. When sharing an image, they can also share the prompt that produced it, allowing another person to reuse the idea with their own photos and details. These controls make review and remixing part of the same creation loop.
GPT-Image-2.5 Flare and Sunburst in the API
OpenAI is releasing two API models under the GPT-Image-2.5 name. They should be treated as separate deployment choices, not as two ChatGPT subscription modes.
| API model | Official positioning | Best fit |
|---|---|---|
| GPT-Image-2.5 Flare | Default choice for most applications; brings the 2.5 quality, editing, and speed improvements, with higher quality than GPT-Image-2 and 50% lower latency | Creator and social content, product experiences, visual search, rapid prototyping, and high-volume generation |
| GPT-Image-2.5 Sunburst | Higher-precision option for detailed creative work, with longer generation times | Production-ready campaign creative and polished product imagery where tighter edit control matters |
Source: OpenAI's ChatGPT Images 2.5 announcement. The announcement does not provide a public price table, resolution matrix, rate-limit table, or benchmark score for either model.
The choice is therefore a workflow decision. Start with Flare when latency and throughput are binding constraints. Evaluate Sunburst when a slower generation is acceptable and the cost of a wrong edit or a drifting product detail is higher than the cost of waiting. Do not infer that Sunburst is universally better: OpenAI positions it for a narrower, higher-control use case.
For implementation details, use the current OpenAI image generation guide and official pricing documentation. Verify the model identifiers and parameters in the developer documentation before deploying, because this announcement page is a product overview rather than an API reference.
Early Independent Observations
Early hands-on reports supplied for editorial review are directionally consistent with OpenAI's positioning. They describe stronger preservation of faces and products when the style, clothing, or setting changes; better handling of nested or recursive compositions; and useful results for Chinese text and traditional illustration styles. They also report visible generation progress in ChatGPT and occasional image noise or small detail defects.
These observations are useful for forming a test plan, not for making universal claims. They come from individual prompts and selected examples, do not establish a controlled benchmark, and should not replace a team's own evaluation. A sensible acceptance set includes reference identity, localized edits, dense text, transparent backgrounds, repeated revisions, and negative cases where the model must leave a neighboring object untouched.
Availability and Safety
ChatGPT Images 2.5 is rolling out to all ChatGPT, ChatGPT Work, and Codex users across desktop, mobile, and web, on all tiers according to OpenAI's announcement. The same announcement states that GPT-Image-2.5 Flare and GPT-Image-2.5 Sunburst are available in the API.
OpenAI says Images 2.5 builds on existing safeguards, including checks on prompts and images. Generated images continue to use C2PA metadata and invisible watermarking to help identify content made with OpenAI tools. Safety behavior and provenance signals are part of the product surface; they are not a substitute for human review of a deployed asset.
Known Limits and Evaluation Checklist
The release announcement does not publish an exhaustive limitations list. Based on the official positioning and early independent observations, evaluate these areas before relying on 2.5 in production:
- Edit boundaries: Does a requested local change leave approved neighboring details untouched?
- Reference identity: Do faces, products, logos, and distinctive features remain recognizable across variants?
- Text and layout: Are all visible words, scripts, alignment, and transparent-background edges correct enough for the intended use?
- Long conversations: Does the asset remain consistent after several sequential edits?
- Latency trade-off: Does Flare's speed or Sunburst's tighter control better match the workflow's constraint?
- Safety and provenance: Are prompt/image checks, C2PA metadata, and watermark signals compatible with the publishing process?
This list is an evaluation recommendation, not an OpenAI benchmark. Proofread and inspect every final asset, especially commercial creative.
Frequently Asked Questions
What is new in ChatGPT Images 2.5?
The release focuses on more faithful reference images, more precise edits, stronger multi-turn consistency, richer handling of complex visual instructions, and up to 50% lower generation latency versus Images 2.0. ChatGPT also adds Sketch, Templates, image comments, and prompt sharing.
What is Sketch in ChatGPT Images 2.5?
Sketch lets you draw a rough visual guide directly in ChatGPT and use it as a reference for the final image. OpenAI suggests room layouts, outfit contours, and doodles as examples; invoke it by typing @Sketch in ChatGPT.
What is the difference between Flare and Sunburst?
Flare is OpenAI's default API choice for most applications and emphasizes quality with lower latency. Sunburst is positioned for detailed creative and editing workflows where tighter control is worth longer generation times. The announcement does not publish enough numeric API specifications to make a broader performance ranking.
Is ChatGPT Images 2.5 available in the API?
Yes. OpenAI lists GPT-Image-2.5 Flare and GPT-Image-2.5 Sunburst as available API models. Check the current developer documentation for exact identifiers, parameters, access requirements, and pricing before integrating.
Does Images 2.5 guarantee perfect image edits or text?
No. OpenAI describes improvements, not a guarantee of perfect isolation or correctness. Review faces, logos, dense text, transparent edges, and every other production-critical detail before publishing.
Should I migrate an Images 2.0 workflow immediately?
Test the workflow first. Images 2.5 is the logical candidate when reference fidelity, targeted editing, or repeated revisions are the binding constraints. Keep a representative evaluation set and compare Flare and Sunburst against the current workflow before changing production defaults.
Use the text-to-image tool to test reference-led generation and iterative edits with the currently available ChatGPT Image models.
