GPT Image 2.5 Prompt Guide With Practical Templates

Start with the result, not the visual mood

“Beautiful cinematic product photo, premium, stunning, 8K” tells the model almost nothing about what the image must accomplish. Is it a square catalog image, a vertical poster, a transparent cutout, a homepage hero, or an edit to an existing photo? Each has a different composition and review standard.

Open with a plain statement of the deliverable:

• Create a square ecommerce hero image for one supplied bottle.
• Edit the room photo by replacing only the white chairs.
• Design a vertical event poster with one exact headline.
• Turn the supplied process notes into a labelled classroom diagram.
• Isolate the supplied object on a transparent background.

That first sentence gives every later detail a job. Lighting supports the catalog image. White space supports the poster's type. Clean edges support the transparent asset. If a description does not help the intended use, it probably does not belong in the prompt.

Use a six-part prompt structure

You do not need the same headings in every request, but the following order is reliable because it separates the result from the decoration:

1. Result: what the image is for and its format.
2. Subject: the people, objects, place, or concept that must appear.
3. Composition: camera position, framing, hierarchy, and empty space.
4. Visible details: materials, lighting, palette, expression, era, labels, and relationships.
5. Exact text: the words that must appear, written verbatim and separated from the rest.
6. Constraints: what to preserve, omit, or leave unchanged.

Create [DELIVERABLE] for [AUDIENCE OR USE].

Subject
[WHO OR WHAT MUST APPEAR, WITH CONCRETE IDENTITY DETAILS]

Composition
[ORIENTATION, CAMERA, CROP, SUBJECT PLACEMENT, HIERARCHY, EMPTY SPACE]

Visible details
[MATERIALS, LIGHTING, PALETTE, ENVIRONMENT, EXPRESSION, ACTION]

Text — exact, verbatim, no extra words
"[TEXT]"

Preserve
[DETAILS THAT MUST STAY UNCHANGED]

Do not add
[UNWANTED OBJECTS, TEXT, LOGOS, WATERMARKS, OR UNSUPPORTED DETAILS]

Output intent
[SIZE OR ASPECT RATIO, BACKGROUND, AND FILE USE]

Concrete does not mean long. “A red chair” is concrete but incomplete. “One low red lounge chair centered against a pale gray wall, photographed straight on, with empty floor space below for a price line” gives the color, count, camera, placement, and layout reason in one sentence.

What happened when we tried the prompt patterns

We used fictional subjects so that the review could stay focused on instruction-following. All five first attempts were usable for the narrow checks below. That is encouraging, but it is a small editorial exercise, not an estimate of how often these prompts will succeed.

The distinction in the fourth row matters. A result can look unchanged to an editor while still being regenerated at the pixel level. If a logo, legal line, pack label, or measurement must be exact, keep that element outside the generative edit and composite it back afterward.

Download the exact five prompts and output hashes if you want to reproduce the checks or adapt them to your own review rubric.

Choose Flare or Sunburst for the workload

OpenAI currently describes GPT Image 2.5 Flare as its fastest model for high-quality everyday image generation and Sunburst as its most capable model for image generation and editing. That is a useful starting distinction, not a guarantee about your image.

If model choice matters to a real pipeline, do not decide from one attractive example. Use the same prompts, references, dimensions, quality, and review rubric for both. The separate Flare vs Sunburst testing guide includes a matched scorecard and a checker whose public template intentionally remains NOT_RUN.

Describe composition as a relationship

Composition prompts work better when they explain where elements sit relative to one another. “Magazine layout” can mean dozens of things. “Place the subject in the lower-right third, leave the upper-left half quiet for a headline, keep the horizon below center, and avoid objects behind the text area” is inspectable.

Useful composition details include:

• Orientation and destination crop
• Camera height, distance, lens feel, and angle
• Number of subjects and their order of importance
• Where the eye should go first and second
• Foreground, middle ground, and background
• Required negative space and what will occupy it later
• Objects that must not be covered, cropped, or repeated

Do not request mutually incompatible camera instructions. “Extreme close-up showing the complete product and wide environment” creates an unresolved choice. Decide which information the frame must prioritize or ask for separate images.

Write product prompts from approved facts

A product image prompt should not invent the product brief. Attach rights-cleared references and name the visible identity details: exact silhouette, cap shape, label layout, material, color, openings, seams, buttons, ports, and what is included. State which elements may change and which may not.

Create a square ecommerce hero image using the supplied bottle photo
as the product-identity reference.

Show one bottle, upright, three-quarter view, centered slightly left.
Preserve the bottle silhouette, cap shape, label proportions, label text,
amber glass color, and every visible seam. Do not redesign the packaging.

Set it on a matte warm-gray surface with a soft shadow. Use a large diffused
key light from the upper left and a restrained edge light on the right.
Leave clean negative space on the right for separately added page copy.

Do not add fruit, water splashes, awards, certification marks, hands,
extra bottles, price text, logos, or performance claims.

In our live check, the fictional amber pump bottle appeared once, the label read HARBOR 18, and the right side stayed open for page copy. The image also avoided the prohibited fruit, plants, splashes, badges, hands, prices, and extra bottles. That does not make generated packaging production-safe: dosage, weight, certifications, ingredients, and regulated copy still belong in a source-controlled design layer.

Separate exact text from art direction

When text must appear inside the image, give it its own section and quote it verbatim. State the number of text elements, their hierarchy, placement, and whether any other writing is allowed. Then check every character in the output; never assume a convincing word shape is correct.

Create a vertical community-workshop poster with a handmade screen-print feel.

Text — EXACT, verbatim, and shown once each
Headline: "MAKE THINGS THAT LAST"
Date: "SATURDAY 18 OCTOBER"
Location: "RIVER ROOM"

Place the headline in the upper third, the date below it, and the location
near the bottom. Use bold, highly legible sans-serif lettering with generous
spacing. Keep the type level and unobstructed.

Visual: one original illustration of a workbench with simple hand tools,
using navy, cream, and muted orange ink textures.

No other words, letters, numbers, signatures, brands, or watermarks.

The poster check returned all three requested strings—MAKE THINGS THAT LAST, SATURDAY 18 OCTOBER, and RIVER ROOM—once each and without extra copy. We would still rebuild business-critical type in a design tool. That makes spelling, kerning, accessibility, localization, and late changes deterministic instead of depending on another generation.

Give every reference image one job

When several references are attached, “use these images” is ambiguous. Identify them by filename or order and assign a role to each: identity, pose, clothing, product, palette, texture, composition, or background. Do not ask the model to infer which reference wins when two disagree.

Use reference 1 for the person's identity and facial features.
Use reference 2 only for the beige jacket.
Use reference 3 only for the gray boots.
Use reference 4 only for the location and camera angle.

Create a new scene of the person standing in the reference-4 location.
Preserve identity from reference 1. Dress them in the jacket and boots
from references 2 and 3. Match the location perspective, but do not copy
other people, text, logos, or temporary objects from reference 4.

If the references conflict, preserve identity first and flag the conflict
rather than blending the subjects.

Use only references you are allowed to use. A technical ability to transfer style, identity, clothing, or layout does not settle copyright, publicity, privacy, trademark, or contractual questions.

Write edits as “change” plus “preserve”

For editing, name the smallest intended change first. Then restate the surrounding details that must remain stable. OpenAI's examples use this pattern for tasks such as replacing one object while protecting camera angle, lighting, shadows, and the rest of the scene.

In the supplied room photo, replace only the two white dining chairs
with simple walnut chairs.

Preserve the camera position, crop, room geometry, table, floor, windows,
wall art, lighting direction, color temperature, contact shadows, and every
other object. Keep the number and placement of chairs unchanged.

Do not add people, decorations, text, logos, extra furniture, or a wider crop.

For the live edit, we asked for only the wall and tabletop to move from warm gray to pale blue-gray. The bottle, pump, label text, position, crop, lighting, and negative space remained visually consistent. We did not treat them as pixel-identical, and neither should a production reviewer. Compare the whole frame after every edit, then use ordinary compositing for anything that cannot drift.

Prompt transparent assets for their real destination

Ask for a transparent background in the generation settings and describe the edge quality you need. Also state the final use: a soft-haired portrait, glass object, icon, fabric product, and hard-edged machine part require different review.

Create one original three-quarter-view hiking boot as an isolated asset.
Show the complete boot with no cropped sole, heel, toe, or laces.

Brown leather, dark rubber sole, neutral studio lighting, realistic material
texture, and a clean silhouette. Keep fine lace openings and sole edges intact.

Transparent background. No floor, shadow rectangle, white fringe, text,
logo, second shoe, foot, or display stand. Leave padding around every edge.

The exported boot was a genuine RGBA PNG with transparent and non-transparent pixels, not a checkerboard painted into an opaque image. It also contained one complete boot, with no floor, logo, stand, or second shoe. For a repeatable file check, use the PNG Transparency Checker or follow the transparent PNG verification guide. Preview edge pixels over white, black, and a saturated color; fine laces, fur, glass, and pale objects often reveal halos that a neutral canvas hides.

Prompt diagrams like an instructional designer

A diagram needs an audience, learning objective, system boundary, labels, direction, and source facts. “Create an infographic about photosynthesis” leaves the model to choose the science and wording. Supply the facts and separate required labels from optional decoration.

Create a landscape classroom diagram for students aged 12–14.
Objective: show the three approved stages in the supplied fact sheet.

Use exactly three numbered panels from left to right. Each panel should have
one flat icon, one short heading, and one sentence. Use only the supplied facts.

Required labels — EXACT:
1. "INPUT"
2. "PROCESS"
3. "OUTPUT"

Use arrows only between adjacent panels. Keep generous white space and high
contrast. Do not add statistics, chemical formulas, dates, extra stages,
mascots, logos, citations, or claims not present in the fact sheet.

Our diagram returned three equal panels in the requested order, with INPUT, PROCESS, and OUTPUT, the numbers 1–3, and two left-to-right arrows. The icons also matched papers, a gear, and a checked document. A classroom diagram still needs subject review for relationships, quantities, scale, and implied causality. For a stricter evidence process, use the Evidence-Locked Infographic Prompt.

Use settings deliberately

The current GPT Image 2.5 documentation exposes model, size, quality, background, and output-format choices. Flare and Sunburst list auto, low, medium, high, xhigh, and max quality settings. The prompting guide also documents custom dimensions subject to current size, aspect-ratio, and total-pixel constraints.

Record these settings with the prompt and references. If you change the model, dimensions, prompt, reference file, and quality at once, you will not know which change fixed—or caused—the result.

Revise one visible problem at a time

Do not answer a flawed image with an entirely new wall of adjectives. Name the problem, the required correction, and what must remain unchanged:

Change only the headline spacing so all three words are clearly separated.
Keep the exact headline text, illustration, colors, paper texture, layout,
date, location, crop, and every other element unchanged.
Do not add or remove any text.

After the edit, compare the entire image with the previous accepted version. Details can drift across repeated generations. When several unrelated parts are wrong, go back to the original reference and a cleaner prompt instead of building a long chain of corrections on a compromised image.

Debug the instruction before adding more style words

Review against a checklist written before generation

Separate three decisions. First, factual acceptance: required objects, text, identity, product details, relationships, and prohibited additions. Second, technical acceptance: dimensions, crop, format, transparency, and downstream compatibility. Third, aesthetic preference: lighting, texture, color balance, and emotional tone. A beautiful image that fails the first two does not advance.

• All required subjects appear exactly once unless repetition was requested.
• Protected identity, product, and layout details remain intact.
• Every word, number, symbol, and label is correct.
• No unsupported claim, logo, watermark, signature, or extra object appears.
• Hands, faces, joins, reflections, and small geometry survive full-size inspection.
• The crop works in the actual destination.
• Transparency and output format are real, not merely visually simulated.
• References and output have the required rights, consent, and approval.

A good prompt is a starting contract, not a magic phrase

The goal is not to discover one secret sentence that always works. It is to make your intent reviewable. A useful prompt tells the model what to build and gives the human a way to say why the result passes or fails.

Keep the first request concrete, give references explicit roles, isolate exact text, pair every edit with a preserve list, and record settings. When the image matters to a product, identity, classroom, publication, or customer decision, retain rejected outputs as well as the final candidate. That record will teach you more about your workflow than another paragraph of mood words.

For matched model selection, continue with How to Test GPT Image 2.5 Flare vs Sunburst. For a difficult document-grounded use case, inspect the textbook-page accuracy benchmark workflow. Neither page substitutes for testing the exact prompt, references, and acceptance rules you plan to use.