GPT IMAGE 2.6 / GUIDE
GPT Image 2.6 Guide: choose the right controls
Start with the task you need to complete. Use this guide to choose a model, write a specific brief and understand the model’s output formats.
Which GPT Image 2.6 model should you choose?
Flare is the starting point for quick ideas and everyday image work. Sunburst is a better fit when you want to spend more time on a detailed composition or a demanding edit. Both variants accept text and image inputs.
Choose the model around the task. A longer request is not automatically better; clear constraints and useful references still matter.
How are quality, resolution and complexity different?
Quality controls rendering detail. Resolution controls pixel dimensions. The OpenAI model also has a separate complexity setting for how extensively the model works through the request.
Use lower quality while exploring and higher quality for selected results. Higher complexity can increase latency and lead to broader changes during editing. Choose settings around the intended output rather than assuming every setting must be maximized.
How do reference images guide an edit?
GPT Image 2.6 uses reference images to guide appearance, composition and style. Assign each reference a clear role and list the details that should stay unchanged.
Use clean, well-lit references. When editing a product, name its shape, color, material and markings. When reusing a character, keep the main reference consistent across requests.
How do you generate or replace text inside an image?
Put the exact words in quotation marks and specify where the words belong. For an edit, name the original words, the replacement and the layout that should remain.
Keep copy concise. Inspect spelling and spacing at full resolution. Precise typesetting and repeated small text still need careful review.
How does editing with markup work?
GPT Image 2.6 can use a transparent PNG annotation layer to interpret circles, arrows and notes placed over the first input image. The annotation image must match the first image’s dimensions.
Keep annotations separate from the original image. Use markup to communicate intent and a mask to define editable regions; the OpenAI API does not accept both in the same request.
How do transparent backgrounds work?
GPT Image 2.6 can generate an image with an alpha channel. Export the image as PNG or WebP when the subject needs to sit over a different background.
Describe a clean silhouette and keep the subject inside the frame. Check edges against both light and dark backgrounds before using the asset in a design. JPEG cannot preserve transparency.
What are GIF animations best for?
GPT Image 2.6 can generate short animated GIFs from text. Simple motion, a stable camera and a clear loop are useful starting points for stickers, reactions and small website animations.
Select GIF in the generator, describe the subject, motion and loop, then generate. Each GIF uses 9 frames at 200 milliseconds per frame, about 1.8 seconds per cycle. Size adjusts to the aspect ratio. Choose Flare or Sunburst and low, medium or high quality. You can also add a still reference image to guide the animation.
When should you choose SVG output?
Choose SVG for static icons, badges and flat artwork that needs editable shapes or crisp scaling. GPT Image 2.6 creates SVG output from a text prompt, one SVG per request.
The generated SVG uses vector paths, shapes and colors. It does not embed raster images, external resources or scripts. Use a short, specific brief and inspect the paths in a vector editor before production use.
What makes a result ready to use?
A usable result meets the brief at the intended display size. Review factual details, readable text, consistent appearance and the exact layout before publishing.
Reference images improve guidance, but repeated generations may still vary. Make one targeted revision at a time. For strict typography or exact placement, finish the final adjustments in a design editor.