20 GPT Image 2.6 Prompts to Copy, With the Right Settings for Each

A GPT Image 2.6 prompt works best when it covers four parts: scene, subject, details and constraints. Scene says where and when. Subject says what the picture is about. Details cover materials, lighting, color and framing. Constraints list what must or must not appear, including exact text.

OpenAI says to use whichever format makes the requirements easiest to read and update, whether that is prose, labeled sections or something closer to JSON. Plain sentences work well for most people. Labeled sections help once a prompt grows past a few lines and you want to change one part without disturbing the rest.

State the purpose as well. A prompt that says "a poster for a jazz festival" gives the model more to work with than "a picture of a saxophone", because a poster implies hierarchy and space for type. Add the aspect ratio in the generator and describe the placement of anything that has to go in a specific spot.

A short prompt is a valid place to begin, and you do not have to fill every part on the first try. Write the subject and the use, look at what comes back and add detail where the model guessed wrong. That costs less than writing a long prompt blind, especially on Standard quality, and it teaches you which words change the result.

GPT Image 2.6 prompts for text work best when the exact wording is in quotes and the placement and typography are described. OpenAI's guide gives the same advice, and adds one more habit: ask for no extra text, then check the result.

Quality matters more here than on most images. OpenAI suggests comparing higher quality levels for small text, dense information or several fonts, so the poster and infographic below start on Ultra with Sunburst. A short chalkboard menu can start lower on Flare, because the lettering is large and the lines are few.

Keep the copy short while you find the layout. Once the composition works, add the remaining lines one round at a time. That makes it obvious which change broke the hierarchy if something goes wrong.

Check the hierarchy as well as the spelling. Name which line is largest and where each one sits, because a model with no instruction may give every line the same weight. Short words in big type are the safest choice for a first attempt, and you can adapt any of these four prompts by replacing the quoted lines and leaving the rest alone.

GPT Image 2.6 prompts for product photos should describe the material, the surface, the light and the lens. Those four details do most of the work of making an object look photographed. OpenAI also lists product imagery among the professional visuals where Flare layout quality has improved.

Say where the product sits in the frame and how much of it should fill the image. "Fills the center third" leaves room for a headline later. Name the direction of the light too, because a shadow falling to one side reads as more natural than an evenly lit object.

If you need the exact shape of a real product, describe its geometry closely and check the result against the original. Before you use an image commercially, compare proportions, label placement and any small print by eye.

Exclusions help a lot in this category. "No logos, no text" keeps invented branding off your object, which matters if you plan to place the image on a real sales page. To adapt a prompt, swap the object and the material first, keep the camera and light language, and only then adjust the background to suit your brand.

GPT Image 2.6 portrait prompts come out best when you specify framing, pose, gaze and light. OpenAI's guide calls out body framing and gaze directly, and those are the details models fill in unpredictably when you leave them out. "Chest up, looking slightly past the camera" gives a far more controlled result than "a portrait of a woman".

For a photographic look, name a lens and a light source. A 50mm lens and window light is a safe starting point. Ask for natural skin texture if you want to avoid an overly smooth finish. For illustrated avatars, drop the camera language and describe outlines and flat color instead.

All three prompts below describe invented people. This site blocks prompts that name a real person, so write the description you want and leave names out.

Clothing and props do a lot of the storytelling in a portrait. Clay on an apron says more about a potter than a line about her job, and a yellow raincoat gives a character something a reader can recognize across a series. If you need the same character again, reuse those exact details in the next prompt, as OpenAI suggests for multi-image work.

GPT Image 2.6 logo prompts should describe the brand, the defining shape and a simple silhouette that stays readable at small sizes. That is OpenAI's own recipe for a reusable logo, and it keeps the model away from the busy, illustrated look that makes a poor mark.

Ask for a transparent background when the logo has to sit on other colors, and choose PNG or WebP as the format. Because complexity plans the composition, Simple is usually enough for one plain shape, while a wordmark with a custom detail can use a bit more planning.

Generate several versions in one go with the image count control, then refine the one you like. Treat the output as a strong concept: look closely at the letterforms and edges, and check that the name is clear to use before you print it on anything.

Keep color and type instructions plain. Name one or two colors at most, and say whether the mark includes a name at all. For a logo you will later edit as vector paths, OpenAI's API also offers SVG output, which suits developers who can call it directly.

GPT Image 2.6 prompts for social media should match the shape of the feed and leave room for what you plan to add. Use 1:1 for most posts and 9:16 for stories and reels, and say where any empty space belongs so that the composition does not fill it.

GIFs are the headline feature of this release, and they suit social posts well. You can write the motion yourself with Text to GIF, or upload one photo in Image to GIF and tap a motion such as Wave, Dance or Laugh. OpenAI's advice is to give the subject a starting pose it returns to, describe one small motion and say whether the camera stays still. The default of 9 frames at 200 milliseconds gives a loop of 1.8 seconds.

Each card below sets a frame count where it matters. More frames cost more credits, so test the motion at Standard quality first, then raise the quality once it loops cleanly. If a campaign needs a series, keep the character description identical from prompt to prompt.

Text on social graphics follows the same rules as on posters: quote it, place it and keep it short. Phone screens make small lettering hard to read, so one short line usually beats two long ones. For a quote card, try the wording at High quality first, then read it at the size your audience will see it.

GPT Image 2.6 sticker prompts need the words "transparent background" and an isolated subject, along with PNG or WebP output. The model supports transparent backgrounds in those two formats, and this site refuses transparency with JPEG so you do not waste credits on it.

A thick white border and a bold outline give the classic die-cut look, and they hide small imperfections along the edge. Describe one subject per image. Sheets of many stickers are harder to cut apart later, and each subject gets less detail.

Check the file when it arrives. OpenAI's guide recommends confirming that a transparent image really has transparent pixels, since a checkerboard pattern painted into the image is an easy mistake to miss on a preview.

Stickers also benefit from a plain subject. A single character with a clear silhouette cuts out cleanly, while wisps of hair, smoke or glass can be hard to separate from a transparent background. If an edge looks rough, simplify the subject or raise the quality one level and run the prompt again.

GPT Image 2.6 Flare fits drafts, simple images and fast iteration, and Sunburst fits final images with more detail, precise layouts or careful edits. OpenAI gives that split in its guide. Start with Flare if response time matters most and with Sunburst if the image needs more detail.

Of the 20 prompts in this article, the chart shows how many start on each model. Flare gets the avatars, icons and social graphics, where a quick draft is usually good enough. Sunburst gets the posters, packaging and portraits, where small flaws are easier to see.

Those are starting points you can change. OpenAI suggests that if Sunburst meets your needs, you test Flare with the same prompts, sizes and quality, then compare results and wait time. On this site both models cost the same credits at the same quality, so the comparison only costs the images you run.

A two-step routine covers most jobs. Run the prompt on Flare at Standard quality until the idea and layout look right. Then raise the quality, or move the same prompt to Sunburst if small text and fine detail still fall short. Because the prompt stays the same, you can see exactly what the change bought you.

The best GPT Image 2.6 settings for most prompts are Standard or High quality while you draft, then a higher level once the layout is right. Complexity defaults to Detailed, so most people only need to change it for simple jobs and small edits. Set the aspect ratio before you generate, because it shapes the whole composition.

The cards in this article use only the settings that fit each job. Text-heavy posters start on Ultra quality because small letters need the detail. Icons and avatars start lower, since they have little fine detail to render. The chart shows how the 20 prompts divide by use.

When you compare settings, change one and keep the rest fixed. That is OpenAI's advice for complexity in particular, and it is the only way to know which setting produced the difference you see.

Aspect ratio deserves a decision at the start, because moving from a square to a tall format changes the whole composition. The table lists the seven ratios in the generator and what each one suits. Format is the last choice: WebP and PNG can be transparent, JPEG cannot, and GIF is the choice for motion.

To fix a GPT Image 2.6 prompt that fails, find the one thing that is wrong and change only that. Rewriting the whole prompt throws away what was working and makes it harder to see what helped. OpenAI's guide recommends one change per round and restating anything that has to stay fixed.

A strange or noisy texture usually responds to better material and lighting language, or to a higher quality setting if small surfaces look muddy. Name the surface ("matte ceramic", "brushed steel") and the light ("soft daylight from the left") so the model has less to guess.

A crowded or confused layout often needs fewer objects and clearer positions. Say what goes in the top, center and bottom. If the model keeps adding things you do not want, list them as exclusions, such as "no logos, no watermark, no extra text".

If you still cannot get a result after a few rounds, simplify the request. Take out half the objects, get a clean image and then add things back one at a time. Models tend to handle a clear scene with two or three subjects better than a long list, and this approach shows you the point at which the image starts to fall apart.