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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsFor image generation, a small, purposeful set of reference images can do more than a long description of every visual detail—if you tell the model what to take from each one. Label each reference by its role, explain how those roles combine, and separate the new scene or edit from the traits that must stay unchanged. References guide the result; they do not guarantee exact fidelity.
What a reference sheet should do
A reference sheet is a compact visual specification, not simply a pile of inspiration images. Each image should answer a different question: who or what is the subject, what style should the result use, which composition or pose matters, or what palette and materials should carry through?
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The accompanying prompt connects those references. It tells the model which traits to borrow, which traits to preserve, and what new result to create. Without that map, the model may blend details in a way you did not intend.
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Choose a few references with distinct jobs
Start with the deliverable you want, then select images that contribute useful and nonredundant information. For example, one image might establish a character’s identity, another a watercolor treatment, and a third a particular layout. A crowded set of similar images can make the intended relationships harder to express.
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OpenAI Academy advises naming uploaded images by order and explaining how they relate, and says a small set is usually easier to manage than a large one. That is vendor guidance, not a universal best number for every model. Google also describes reference images for style, color, composition, character consistency, and combining a product with a new setting.
Build the prompt in layers
Write the request so the model can distinguish the new task from the visual information supplied by the references. Include only the details that shape the result or prevent a likely mistake.
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- Goal: Identify the deliverable or intended use.
- Subject and action: Say who or what appears and what is happening.
- Scene and framing: Describe the setting, viewpoint, composition, and spatial relationships that matter.
- Reference map: Label each image and state which traits it contributes.
- Invariants: Name the identity, layout, object, or visual qualities that should remain consistent.
- Change: State the new scenario or the specific edit.
- Exclusions: Mention unwanted text, logos, objects, or background elements when relevant.
Google’s prompt guidance offers a useful blank-canvas scaffold—subject, action, location or context, composition, and style. For reference-guided work, add the references, explain their relationships, and then state the new scenario. These are practical structures, not required syntax.
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Example: combine a character and a style reference
“Create an illustration of the character waiting at a train station. Image 1 is the character reference; keep the same face and clothing. Image 2 is the watercolor style reference; use its palette and brush texture. Show the character in a three-quarter view beside a platform sign.”
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This is a suggested prompt pattern, not a guarantee of a particular output. Its useful feature is the explicit division of labor: one image supplies identity, the other supplies style, and the text supplies the new scene.
For edits, separate what changes from what stays fixed
When editing an existing image, state the requested change narrowly and list the important elements to preserve. For example: “Change only the jacket color to deep green. Keep the person’s identity, pose, framing, and background.”
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Make one targeted revision at a time, then inspect the result. If the subject is right but the lighting is wrong, ask for a lighting adjustment while restating the important invariants. OpenAI Academy recommends clear preservation instructions and small, targeted refinements; Google’s guidance also recommends reviewing the output and adjusting particular aspects such as color, lighting, or objects.
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If the model mixes up references or changes details you wanted to preserve, avoid adding a longer list of loosely related instructions. Try a narrower prompt:
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- Restate only the references that matter to this revision and the role of each one.
- Remove redundant references that do not contribute a distinct trait.
- Identify the specific feature that drifted and say what should remain fixed.
- Change one variable, then review the new result before asking for another change.
A reference-guided workflow can reduce how much visual detail you need to describe from scratch, but it does not ensure identical results across generations or tools.
Reference-image features vary by tool
OpenAI, Google, and Adobe document overlapping workflows, but their interfaces and controls are not interchangeable. Check how a tool accepts multiple images, whether it distinguishes style from composition, and whether its editing workflow lets you specify what should remain unchanged.
| Tool | What its official guidance describes | What to check in your workflow |
|---|---|---|
| ChatGPT and OpenAI image tools | OpenAI describes multiple images for generation or editing, with prompts that identify images by order and explain their roles. Its Academy guidance recommends concise prompts and targeted revisions. | How to upload and refer to multiple images, and how to state the edit and preservation instructions. |
| Google image tools | Google describes references for style, color, composition, character consistency, and combining a product with a new environment. | Which reference types and controls are available in the specific Google product and account. |
| Adobe Photoshop | Photoshop Help describes reference-image choices for style or composition. | Which reference option fits the edit and how it works alongside Photoshop’s image-editing controls. |
These are vendor feature descriptions, not independent image-quality tests or a neutral ranking. Availability and interface steps can vary by product, account, and region. For API use, OpenAI’s image-prompting documentation identifies GPT Image 2 as supporting generation and editing, including text rendering and reference-based edits; model names and lifecycle details can change.
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OpenAI Academy’s April 10, 2026 guidance says that “in most cases, 1–3 clear sentences are enough.” That is OpenAI’s recommendation, not a measured universal limit. A compact request works when it clearly assigns roles and preserves the right traits; add detail when the scene or edit genuinely needs it, rather than describing every visible element by default.
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