ChatGPT Images 2.5 · Sketch, Editing and Thumbnails in Practice

Quick Summary

• Credit: Video, tests and images shown belong to Paul J Lipsky. Editorial organization, official verification, and supplemental prompts are by JQ VISIONS.
• OpenAI released ChatGPT Images 2.5 on September 8, 2026 with Sketch, image comments, templates, better reference fidelity, multi-turn editing, and faster generation.
• Availability for all levels of ChatGPT, ChatGPT Work and Codex is official information. In the video, Paul initially presents free access as an assumption, so this article replaces the uncertainty with confirmation published by OpenAI.
• Sketch works best when the drawing defines spatial relationships and the text explains the meaning of each shape. Without a caption, the model still inferred a plausible room, but reinterpreted some objects.
• Comments and markings allow you to pinpoint an area without describing coordinates. In one of the tests, the system changed the wrong plan, showing that the visual mark guides the editing but is not a pixel-perfect mask.
• The erase tool correctly removed a plant after the zone was marked. The result demonstrates semantic editing: the interface signals the intention and the model reconstructs the background.
• Background removal failed in a room full of objects and worked well in a portrait with clear separation between person and scene. The quality largely depends on the legibility of the silhouette.
• A childhood photograph maintained the face and pose by removing reflection and changing the clothes for a suit. The garden simulation also preserved the site, but exaggerated the amount of stone and would need a round of moderation.
• The photographs of the two dogs maintained individual characteristics during changes in pose, style and removal of harnesses. It was the most convincing example of identity consistency in the video.
• The thumbnail started as a sketch and went through several changes without visibly degrading the creator's face. The result suggests a strong workflow for guided layouts, as long as text, crop and identity are audited before publishing.

A practice test with room to fail

Paul J Lipsky approaches ChatGPT Images 2.5 as a user, not as a laboratory benchmark. Try new tools, react to the results and show both successes and mistakes. This transparency makes the video especially useful for understanding how the interface behaves in a real creative session.

OpenAI describes Images 2.5 as an upgrade with sharper details, more natural lighting and texture, better subject preservation, localized editing, and up to 50 percent less latency than Images 2.0. Paul's results are examples compatible with this proposal, but a single run does not measure the overall success rate.

The article uses three implicit labels. OpenAI information is official specification. What appears on the screen is the creator's test. Process recommendations are JQ VISIONS editorial review. This separation avoids turning legitimate enthusiasm into a product promise.

How to recognize access and what is confirmed

In the video, Paul looks for the updated indication next to the Images area and the logo template as signs that the new experience has arrived at the account. The interface may change, so these indicators should be treated as clues for that launch, not as permanent navigation.

The creator assumes that all users include the free tier. The official page removes the doubt: Images 2.5 has started to be distributed to ChatGPT, ChatGPT Work and Codex users at all levels, on desktop, mobile and web.

Rollout does not mean simultaneous availability on all accounts or platforms. If a tool does not appear, update the application, open the Images area, and check the current documentation or release notes before concluding that there is a problem.

Sketch to Image: the drawing controls the composition

Paul draws a room with a brown sofa, large windows, a dog on the rug and a television on the wall. The design is deliberately rudimentary. Then it adds a description that explains the role of each shape. The result maintains spatial organization and transforms simple symbols into a coherent division.

In a second attempt, send a similar sketch without explanation. The model still identifies sofa, dog and television, but reinterprets part of the composition. The test shows the ideal division of labor: the sketch communicates position, scale and relationship; textual instruction communicates identity, material, style, and priority.

Don't try to draw every detail. Use simple blocks, leave room for framing, and create a small caption when colors or shapes might be confusing. Also say what is mandatory to preserve and what can be invented.

OpenAI confirms that Sketch can be launched with @Sketch in ChatGPT and used as a visual guide for layouts, clothing or doodles, accompanied by a description of the desired style and details.

Comments and markings: accurate but not infallible

After the first room, Paul points to an empty area and asks for a cat. The model places the animal in the expected location. It also accumulates several comments before sending: a dead plant, a rainbow outside and gray walls.

Two changes work, but the system kills the wrong plant. It's an important limit. The API documentation itself explains that a mask serves as guidance without guaranteeing exact shape tracking. In the ChatGPT interface, treat tagging in the same way: it reduces ambiguity, but does not replace verification.

The erase tool is also semantic. The marked area does not disappear immediately. The model interprets the object and reconstructs the surface that would be behind it. In the test, the plant on the table is successfully removed.

For client work, make one critical change per round. Write replace only the highlighted object and list the elements that should remain. Compare the new version with the old one, especially around the edges of the markup.

Background Removal: Choose the Right Image

Applying background remover to the room produces a strange result because the scene has furniture, plants, windows, depth, and several candidates for the main subject. The order does not contain an unambiguous silhouette.

In a portrait with a clear separation between person and background, the same tool works much better. Visual contrast, contour continuity and the absence of overlapping objects make the problem simpler.

Before removing the background, decide what the subject is and check hair, fingers, translucent clothing, glass, and shadows. For compositing assets, confirm that the file has true transparency and not just a checkerboard pattern drawn on the image.

Childhood photography: cleaning, dressing and preserving identity

Paul sends a printed photograph of himself as a child and asks to remove the reflection and dress the boy in a suit. The result preserves pose, framing, face and environment, while altering clothing and surface quality.

This type of editing is a good test of fidelity because the source image may have noise, reflections, low resolution and aged colors. Don't ask for restoring, colorizing, reframing and changing clothes in a vague instruction. List changes and invariants separately.

Photographs of children and family archives deserve additional care. Only use images you can process, avoid publishing personal data, and keep the original out of the edit chain. A generated reconstruction is an interpretation, not a neutral documentary restoration.

Visualize a garden without confusing concept with project

A photograph of the backyard is transformed into a proposal for a stone garden. The general structure is preserved and the image offers useful ideas, but the result has too much stone. The creator himself identifies the need to reduce intensity.

To obtain a more plausible simulation, define an approximate percentage of the area to be changed, permitted materials, circulation zones and elements that cannot disappear. Ask for a minimal, moderate, and bold version rather than relying on a single interpretation.

A generative image helps discuss direction, it does not replace surveying, drainage, budgeting, safety or landscape design. Use it as a concept board and validate the execution with professionals when there is real work.

Templates reduce the blank page, do not eliminate the brief

The new gallery includes formats such as logos, posters, illustration and interior design. OpenAI presents templates as starting points for popular formats to which the user adds information, visual elements and style.

In the interior test, Paul uses photographs and plans of a house found on a real estate portal. The first result does not match the layout you expected. Only after sending a capture of the desired format does the system build a visual presentation closer to the intention.

The lesson is simple: the name of the template does not alone define the deliverable. Indicate final format, number of panels, hierarchy, labels, proportion and type of information. For your own projects, use photographs and plans that you own or have a license for, rather than reusing images from advertisements without permission.

Two dogs, several editions and identity preserved

Paul uploads photos of his two dogs for the illustration template. The first result preserves the animals in a recognizable way. Then he asks them to appear hugging a blanket and, in a new edition, he removes their harnesses.

Over rounds, relative size, fur color, face shape, and other distinguishing features remain stable. For the breeder, it's one of the best results he's seen in animal consistency, an area where models often mix patterns and proportions.

To repeat the process, provide a clean reference for each animal and identify them by unambiguous names or descriptions. Write a short sheet of invariants and repeat only the features that cannot be derived. Then change one variable at a time: pose, setting, accessory or style.

Official documentation states that Images 2.5 better preserves subjects from reference photographs and maintains previous changes during long conversations. The dog test is an example of the breeder illustrating this ability, not a guarantee for all breeds, poses or benchmark qualities.

Thumbnail with Sketch and multiple rounds of editing

To finish, Paul draws the structure of a thumbnail: text position, logo and main image. The model converts the sketch into a layout and the creator continues to adjust the result by conversation.

The face remains recognizable over several editions, without the progressive deterioration that Paul has seen in other generators. It's an especially useful combination: Sketch for composition, authorized photography for identity, and multi-turn editing to explore text and hierarchy.

Still, a thumbnail needs to work at a small size. Check text letter by letter, contrast, distance between face and title, safe areas, crop on mobile and readability at around 10 percent of the original size. Generate the concept, but finalize critical typography in an editor when you need absolute control.

Reusable workflow for conversational authoring

Start with the goal and final format. If the idea depends on composition, make a sketch. If it depends on identity, upload authorized references. Then list invariants and describe the first change concretely.

Save each approved version. Use comments to locate an area, but repeat in the text which object you want to edit. Make one major change per turn and revert to the last clean version when drift appears.

Finish with an audit: identity, anatomy, text, outlines, transparency, duplicate objects, intensity of change, rights and output dimensions. The value of Images 2.5 is not to dispense with editing, but to shorten the distance between a visual intention and a basis good enough to decide, refine or produce.