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For the most reliable result, give the image generator the exact, short wording and specify its location, style, size, and color. If the wording must be exact, the text is small, or the layout contains substantial copy, generate the image without relying on the model to typeset everything and add or polish the text in a design editor. Then inspect the result and make one targeted correction at a time.
Choose the right way to handle the text
AI-generated lettering can come out misspelled, distorted, crowded, or hard to read. A precise prompt can make the intended wording and appearance clearer, but it does not guarantee perfect text. The practical choice is whether to ask the image generator to draw the lettering, edit a specific area of an existing image, or place the final typography in a design tool.
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Use generated lettering when the words are short and the visual treatment matters as much as exact typography—for example, a brief title on a poster concept. Prefer a separate text layer in a design editor when every character must be correct, when the image contains multiple labels or paragraphs, or when the text is too small to inspect comfortably. OpenAI’s guidance recommends considering design-tool polishing for dense layouts or heavy in-image text. OpenAI Academy’s image-generation guidance states: “For dense layouts or heavy in-image text, emphasize ‘sharp text rendering,’ and consider polishing in design tools if needed.”
Decide before generating
- Short, prominent wording: Try a literal prompt with a clear placement and typography description.
- Exact copy or dense information: Create the visual first, then set the wording in a design editor where you can check and revise it directly.
- A mostly correct image with one bad text area: Use an edit workflow that targets that area, if your tool supports it, rather than requesting a wholly new composition.
- Small or complicated text: Inspect carefully at full size and consider a design-tool finish; a result that looks plausible at thumbnail size may not be readable.
Separate the visual brief from the copy brief
It helps to think of an image with lettering as two jobs: making the visual and setting the words. The visual brief describes the background, subject, composition, and mood. The copy brief states the exact wording and its typography and placement. Keeping those instructions distinct makes it easier to spot whether an error is in the image concept or the lettering. If the copy is substantial, make the visual first and typeset the words separately rather than asking one generation step to solve both jobs.
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Before starting, decide which parts of the result are flexible and which are not. A decorative title might tolerate a slightly different visual treatment, while a name or required headline cannot tolerate a spelling change. This distinction helps determine whether to try another prompt, use a local edit, or move the words to an editable design layer.
Write a more precise text prompt
Replace vague directions such as “make the text look good” with the wording and visual constraints you actually need. OpenAI’s guidance recommends specifying the exact phrase, often in quotation marks or capitals, and describing the font style, approximate size, color, and position. Keep the wording short, and spell uncommon names letter by letter. OpenAI Academy and the OpenAI API image-prompting guide both describe these prompt-level controls.
A prompt pattern to adapt
For a new image, write the requested text as a distinct instruction. For example:
Create a clean event poster with a warm orange background and a simple illustration of a microphone. Include the exact headline “NORTHSIDE MUSIC NIGHT” at the top. Use bold, simple, white sans-serif lettering, large enough to read, centered across the top. Include no other text, logos, or lettering.This pattern makes the copy literal and separates it from the visual description. Change the words and design details to fit the image; do not add extra text unless you want the model to attempt to render it. “Large enough to read” is useful as an instruction, but it is not a measurable guarantee, so check the actual image.
Make the request unambiguous
- Quote the exact copy. Do not ask for a slogan or label without stating its exact wording if the words matter.
- Describe where it belongs. Use a location such as “at the top,” “in the lower-right corner,” or “centered on the sign.”
- Describe the treatment. Specify a style, approximate size, and color. If the type should be plain and readable, say so rather than relying on a broad mood description.
- Limit additional lettering. When appropriate, say “include no other text” or “no logos.” This can clarify what should not appear, though it does not guarantee that unwanted marks will be absent.
- Spell unusual words explicitly. For an unfamiliar name, give the letters individually—for example, “Spell the name R-I-V-A exactly.”
For a change to an existing image, identify both the requested change and the elements that must remain as they are. The OpenAI API guide discusses image editing as well as generation; state the specific text change and make preservation constraints explicit, such as “replace only the headline; keep the illustration, colors, and layout unchanged.”
Use a repeatable prompt-and-review sequence
- Write down the final copy first. Make sure you know the exact phrase before generating. Remove optional words if they are not necessary, since shorter wording is easier to specify and inspect.
- Describe the appearance and position. Include the approximate size, color, font style, and location. If the text belongs on an object, identify that object as well as the location—for example, a headline at the top of a poster or a label centered on a sign.
- Say what must not change. When editing an existing image, identify the text area to change and name important visual elements to preserve. Add a no-extra-text or no-logo constraint if unwanted lettering would cause a problem.
- Generate or edit, then inspect the whole image. Compare the visible words to the copy you wrote down and check whether the composition still suits the task.
- Choose the next action based on the error. A near-correct local problem may justify one focused edit. A misspelling in exact copy, dense information, or repeated failures is a reason to set the typography in a design editor.
This sequence is deliberately conservative: a prompt can communicate the intended text and design, but it cannot certify the result. Treat each generated version as something to review, not as final copy that has been proofread for you.
Inspect the output before accepting it
Check the generated image against the intended copy, character by character. Confirm spelling, capitalization, spacing, and whether the text is legible at the size and orientation where it will actually be used. A headline may be readable when enlarged but fail at its intended display size; dense or small text deserves particular scrutiny.
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- Compare every visible word with the exact wording in your prompt.
- Check that letters are distinct, not merged, broken, or shaped into different characters.
- Look for extra lettering or marks that were not requested.
- Confirm that the text is in the intended location and does not obscure important parts of the image.
- Judge readability at the intended viewing size, not only while zoomed in.
The OpenAI API image-prompting guide suggests comparing medium- or high-quality settings when an image has small text, dense information, or multiple fonts. Treat this as a reason to inspect those settings for your particular task, not as a claim that a quality setting will ensure correct spelling. Model names and available options can change; check the current guide for the tool you are using.
A final-text checklist
Before using the image, review it as both artwork and copy. Confirm that the words are present exactly as required, that no extra lettering has slipped into the image, and that the text is actually readable at its intended size. Then check that the type sits in the requested location and does not cover an important part of the illustration. For a layout with several labels or more than one font, inspect each text element individually; do not assume that one readable headline means every smaller element is correct.
If the image is meant for a particular use, evaluate it in that context rather than relying only on a zoomed preview. The key question is not just whether the letters look plausible, but whether a viewer can read the intended words at the size and orientation in which the image will appear. If you cannot confidently verify a word, do not treat it as final exact copy.
Fix errors with one deliberate change at a time
If the result is close, make a focused revision instead of repeating the entire request with several new ideas. OpenAI Academy advises: “The best way to improve an image is usually through small, targeted revisions.” A targeted instruction makes it easier to see whether the specific change helped and reduces the chance that unrelated parts of the composition drift.
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Examples of targeted corrections
- Wrong spelling: Restate the correct phrase exactly and ask to replace only the misspelled text.
- Text is too small: Ask for the same wording in larger lettering while specifying that its position and the rest of the composition should stay unchanged.
- Text is hard to distinguish: Request a specific color or simpler font treatment, keeping the copy literal.
- Unwanted words appeared: Specify that only the required phrase should be present and that no other text should be added.
- The composition changed during a correction: Restate the important elements to preserve and narrow the requested edit to the text area.
For a local correction, use an existing-image edit or a selection/markup feature if available. OpenAI’s image guidance covers iterative editing, while Adobe’s Firefly Markup instructions describe using a freehand drawing or region selection together with a text prompt to direct an edit to a particular part of an image. The exact controls depend on the product and its current interface.
When a local edit is worth trying
A local edit makes sense when the image is otherwise usable and the unwanted or incorrect lettering is confined to a particular area. If the tool offers a selection or markup control, use it to direct attention to that region, then describe the requested change in plain, specific terms. Keep the scope narrow: say what lettering to replace or remove and what nearby elements should remain unchanged.
After the edit, check not only the new word but also the boundary around the edited region and the rest of the image. A local instruction is a way to direct an edit, not a guarantee that every other pixel will remain identical. If the correction keeps disturbing the composition, or the text must be exact, switch to direct typography editing rather than repeating broad regeneration requests.
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When to use a design editor instead
A design editor is the safer finishing step when exact copy matters more than having every letter generated as part of the image. Generate the background, illustration, or overall composition, then add the final wording as editable typography. That separates the visual-generation task from the copy-setting task: you can check the spelling directly, adjust placement and size, and revise the words without asking the image generator to redraw them.
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This is especially useful for paragraphs, multiple labels, small-print information, or text that must match supplied copy exactly. It is also a practical fallback when repeated image edits keep changing the composition or failing to correct a particular character. The sources do not establish a universal error rate or a model that always renders text best, so choose the workflow based on how exact and readable the finished text needs to be.
Adobe Firefly Boards text editing
Adobe documents a Generative Text Edit feature in Firefly Boards that detects text on the same baseline as one editable line and lets the user modify or delete it. It may help with straightforward horizontal Latin text, but it is not a universal repair method. Adobe lists limitations involving emojis, non-Latin characters, skewed or rotated text, heavily stylized 3D lettering, overlapping elements, and substantially different font sizes. Availability also depends on the product and model. See Adobe’s Generative Text Edit instructions for the current feature details and supported models before building a workflow around it.
If the text falls outside those documented strengths, or the tool cannot make the exact correction you need, use a conventional editable text layer in a design editor instead. Do not assume an automatic text-edit feature will recognize every script, orientation, or decorative treatment.
Understand what automatic text editing can and cannot do
Adobe’s documented feature is most relevant when the lettering is a clear, horizontal Latin line that the tool can detect on a shared baseline. Its limitations matter before you choose it: emojis and non-Latin characters may not be supported, nor may skewed or rotated text, heavily stylized 3D lettering, overlapping elements, or lettering with substantially different font sizes. If a design combines several of these characteristics, do not assume the feature will identify each item as editable text.
Adobe’s Generative Text Edit page is dated March 17, 2026, and its Markup instructions are dated June 9, 2026. Those dates identify the documentation, not a guarantee that a feature will remain available in the same form. Check the current interface and supported models before relying on either workflow. For a task outside the documented limits, a conventional design-editor text layer is the more direct way to set and check the wording.
Choose a workflow by the job, not by a model ranking
Official product documentation describes capabilities and limitations, not a controlled head-to-head scorecard. There is no basis here for claiming that one current image model is always the best at text. Compare tools against the work you need to finish:
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| What to compare | What to check | Why it matters |
|---|---|---|
| Exact wording control | Can you provide literal copy, check the output, and correct a misspelling? | The prompt can clarify the intended words, but a separate editable text layer provides a direct way to set and verify final copy. |
| Generation or editing | Does the workflow create a new image, edit an existing one, or both? | A local text problem may call for an edit rather than a new composition. |
| Localized changes | Can you select or mark an area and ask for only that region to change? | Targeting a region can help direct a correction while preserving the rest of the image. |
| Text format support | Does the workflow suit the needed script, orientation, styling, and amount of text? | Documented text-edit tools may have limits for scripts, rotation, overlap, or decorative effects. |
| Final correction and checking | Can you revise the words directly in a separate design layer? | Exact copy and dense layouts are easier to check when the final typography is editable. |
Use these criteria to compare the actual workflow rather than relying on a general claim about which model is “best with text.” A tool may be useful for making a visual concept, another may offer a convenient local edit, and a design editor may be the right place to finish the exact words. The practical choice depends on whether you need a new composition or a correction, how much text the image contains, and whether the needed script and treatment fit the editing feature.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Troubleshoot common text-rendering problems
The text is misspelled
Put the intended phrase in quotation marks or capitals, remove unnecessary copy, and explicitly spell any unusual name letter by letter. If another attempt still fails and the wording cannot be wrong, stop asking the generator to typeset it and place the text in a design editor.
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Make the requested text larger, name a clear font style, and state its color and placement. Inspect at the intended display size. If the text remains too small, crowded, or visually tangled, use a design-tool finish rather than relying on another broad prompt.
Only one part of the image needs repair
Use an existing-image editing workflow and describe the local change. If supported, select or mark the affected region; Adobe’s Markup documentation describes this approach. State what must remain unchanged so the edit request is not mistaken for a request to redesign the whole image.
A text-editing tool cannot recognize the lettering
Check whether the text is horizontal, Latin, clearly separated, and not heavily stylized or overlapped. Adobe’s documented Generative Text Edit limitations cover several cases where recognition may not fit the task. For unsupported scripts or treatments, or text with substantial size differences, use direct typography editing in a design tool.
Each revision changes something else
Reduce the request to one correction, identify the area to change, and restate the key composition details to preserve. Avoid bundling spelling, color, layout, and illustration changes into one instruction; separate requests make it easier to assess each result.
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Image-generation models, quality options, and feature availability change. The OpenAI API image-prompting guide describes gpt-image-2 and image generation and editing; it also lists GPT Image 1.5 as scheduled to shut down on December 1, 2026. Because that schedule and available options are time-sensitive, verify the current documentation before choosing a model or building a workflow around it. The guidance on literal wording, focused revisions, and design-tool finishing is more durable than any particular model name.
OpenAI Academy’s “Creating images with ChatGPT” page is dated April 10, 2026. Its practical recommendations are to state exact wording and visual details, and to use small, targeted revisions. Treat these as workflow guidance rather than a promise of perfect output: the cited documentation does not provide a controlled text-rendering error rate or establish a universally superior model.
Frequently Asked Questions
Can a prompt guarantee that AI-generated text will be spelled correctly?
No. Exact wording in quotes or capitals, short copy, and clear typography and placement instructions make the request more specific, but they do not guarantee perfect lettering. Inspect the result character by character. For copy that cannot contain errors, add it as editable text in a design editor.
What should I include in a prompt for text in an image?
State the exact phrase, where it should appear, and its approximate size, color, and font style. Keep the wording short, spell unusual names letter by letter, and specify when no other text or logos should appear.
Can I fix text in an image without regenerating the whole image?
If the tool supports editing an existing image, request one local change and state what should stay fixed. Selection or markup controls can help direct the edit to a particular region. Check the result afterward, since a local edit does not guarantee that everything else will remain unchanged.
Which text can Adobe Firefly Boards Generative Text Edit handle?
Adobe documents detection of text on the same baseline as one editable line, and says the feature is suited to clear, horizontal Latin text. Its listed limitations include emojis, non-Latin scripts, skewed or rotated text, heavily stylized 3D text, overlapping elements, and substantially different font sizes. Check the current feature interface and supported models.
Should I choose an image model based on text-rendering rankings?
The cited official documentation describes capabilities and limits, not a controlled head-to-head ranking or a model that is always best at text. Compare exact-wording control, existing-image editing, local-change precision, script and layout support, and whether you can correct the final copy in a separate design layer.
The Bottom Line
For short, prominent wording, give the generator the exact phrase and specify its style, size, color, and position. Inspect every character, then make one targeted edit at a time. For exact copy, small text, or dense layouts, generate the visual and add the final typography in a design editor.
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