Text in generated images used to be a punchline. It mostly works now — and the ways it still fails are specific enough to plan around.
- It got fixed deliberately. Text rendering is now a named feature vendors build and advertise, not an accident of scale.
- Short is reliable, long is not. A few words on a sign usually work; a paragraph on a packet usually does not.
- Quote the exact string. Put the words in quotation marks and say where they go — describing them is how you get near-misses.
- The failures are predictable: extra letters, plausible-but-wrong spelling, and drift in the second and third lines.
- For anything that must be correct, do not generate the text at all. Generate the image, set the type on top.
- Always read it out loud before publishing. Your brain autocorrects text in images, which is exactly why these errors ship.
The model is not typing. It is drawing shapes that look like letters, the same way it draws a hand — and it is drawing them from having seen a great many pictures of words.
That is why it can get a familiar word perfect and an unusual one almost right. A brand name it has seen a million times is a shape it knows. Your client's name is not.
What works now
Text became a feature, not an accident
The improvement was engineered rather than emergent. Vendors now list text rendering as a headline capability — OpenAI's ChatGPT Images 2.0, released in April 2026, was announced with improved text rendering and multilingual support among its named improvements.OpenAI, "Introducing ChatGPT Images 2.0" (openai.com), released 21 Apr 2026; improved text rendering and multilingual text listed among the model's stated capabilities. Which model is best at text changes with every release, so this page names a documented example rather than ranking models. Checked 31 Aug 2026
The practical consequence: stop assuming it cannot do text. The assumption is a year out of date, and it makes people rule out approaches that now work.
Length is the variable that matters
Reliability falls off with the amount of text, sharply.
The rule that falls out of it: if the words matter more than the picture, this is the wrong tool for the words.
How to ask for it
Quote it, place it, describe it
Three parts, and most failures are a missing one.
Quote the exact string. Write the sign reads "OPEN LATE" rather than a sign advertising late opening. The second invites the model to invent wording, and it will.
Say where it sits. On the awning, across the top third, on the front of the packet. Unplaced text lands wherever there is room, which is often across your subject.
Describe the lettering as an object. Painted, embossed, neon, vinyl, chalk — plus a rough style. This anchors the rendering to a physical thing rather than a font idea.
Ask for less text than you want. Two words rendered perfectly beats six rendered nearly.
The failure modes, and what each means
When not to generate the text at all
For anything that has to be correct, generate a clean image and set the type on top. A price, a phone number, a legal line, a brand name, a URL.
This is not a workaround. It is better in every dimension: the text is selectable, searchable, translatable, readable by a screen reader, correctable without regenerating, and typographically controlled. It also cannot be subtly wrong.
Prompt for the space rather than the words — "clean unmarked awning with room for a sign", "plain packet front, no lettering" — then place real type in the gap. Is your AI output usable? covers why baked-in text is an accessibility problem as well as a production one.
Read the text out loud, letter by letter, before it ships.
Reading silently does not work. Your brain corrects near-miss words automatically — which is precisely why misspellings in generated images get published by the person who made them and spotted by everyone else. Spelling it out loud defeats the autocorrect.
Before you publish an image with words in it
OpenAI, "Introducing ChatGPT Images 2.0", released 21 April 2026 — improved text rendering and multilingual support are the vendor's own stated capabilities. Checked 31 August 2026.
This page ranks no models and quotes no accuracy rate. Which model renders text best changes with each release, and a league table here would be stale within weeks. The failure modes and the fixes are the durable part — they follow from the fact that the model is drawing letterforms rather than setting type, and that has not changed. The prompting advice is craft, reasoned from those failure modes rather than measured in a controlled test.
The through-line: it can draw words now, but it is still drawing them. Anything that has to be right belongs in real type on top of the picture.