How to Get AI Image Generators to Render Text Correctly

Type a birthday sign, a menu board, or a chart title into most AI image generators and you'll get something that looks like text from across a room — the right shape, the wrong letters, maybe a word that dissolves into gibberish halfway through. That's been true of AI image tools since the first diffusion models, and it's the single biggest reason people still open Canva or Photoshop to finish a graphic instead of trusting the AI output as-is.

That's changed enough in the last few months that it's worth revisiting. Google's Nano Banana Pro (the Gemini 3 Pro Image model) and OpenAI's newly updated ChatGPT Images 2.5 both treat text as something closer to typography than texture, and they get it right often enough now that a poster, an infographic, or a product label is a realistic AI-first task rather than something you generate and then rebuild by hand. But only if you prompt for it correctly — the default "add text that says X" approach still fails more than it should.

Why AI-generated text breaks in the first place

Older image models learned to draw letters the same way they learned to draw everything else: as visual patterns copied from training images, not as characters with a fixed spelling. A model that has seen thousands of coffee shop signs learns what a sign generally looks like — serif-ish shapes, roughly the right word length — without ever representing the actual string "OPEN" as a sequence of four letters it needs to reproduce exactly. That's why AI-generated text often nails the font style and layout while getting individual letters wrong, especially past the first word or two.

Newer models close this gap by reasoning about the text as symbolic content — the literal characters and their order — before rendering it into the scene, closer to how a layout tool places type on a canvas than how it paints a texture. That's the real reason text rendering has gotten noticeably better, and it's also why how you write the prompt matters more than which model you pick.

Rule 1: Give it the exact text in quotes, not a description

"A sign that welcomes customers" leaves the model to invent wording, which is where mangled letters creep in even on models that are otherwise good at text. Put the literal string you want in quotation marks instead: a sign with the text "WELCOME, WE'RE OPEN" rather than a sign welcoming customers. Quoting the exact phrase tells the model there is a specific string to reproduce, not a vibe to approximate.

Rule 2: Keep the total text short, and split up anything long

Text accuracy degrades the more of it you ask for in a single image. A three-word headline renders far more reliably than a paragraph of body copy crammed onto a poster. If you need more than a short headline and a line or two of supporting text, split the job: generate the graphic with just the headline first, confirm it reads correctly, then either generate a second pass for supporting text or add the smaller copy in a design tool afterward. Treat any AI image generator like a headline machine, not a desktop publishing app, and you'll get fewer garbled results.

Rule 3: Name the font, don't just imply a style

"Modern sans-serif," "bold condensed," or "a rounded font like a children's book cover" gives the model a concrete typographic target instead of leaving font choice to chance alongside everything else it's rendering. You don't need the exact typeface name — a plain description of weight, spacing, and character shape (bold, wide letterforms, tight tracking) is usually enough to keep the output legible and on-brand.

Rule 4: Write the copy before you write the image prompt

A trick that consistently improves accuracy: settle on the finished wording as its own step, separate from describing the scene. Ask the model (or write it yourself) for the exact headline or label text first, lock that down, and only then build the full image prompt around that confirmed string. Bundling "come up with a catchy tagline" and "now render it on a poster" into one request gives the model two hard jobs at once — copywriting and typesetting — and rendering accuracy tends to suffer when both happen in the same breath.

Rule 5: For infographics, spell out layout, not just topic

An infographic prompt that just says "make an infographic about our Q3 results" forces the model to invent a layout, a chart type, and a color scheme on the fly, on top of getting numbers and labels right. Specify the structure instead: how many sections, what each one covers, which chart type per data point (bar, donut, a big single number), and your actual brand colors as hex codes if you have them. A prompt like "a 3-section infographic: a donut chart for market share labeled '42%', a bar chart comparing Q2 vs Q3 revenue, and a callout box with the number '128 new customers' in #1B4B43 green" gives the model far less room to improvise wrong text into the gaps.

Rule 6: Reuse the same reference image or seed across a set

If you're producing more than one graphic in the same campaign — a set of social tiles, a slide deck, a run of product labels — regenerating each one from a fresh prompt invites font, color, and layout drift between them, on top of text accuracy issues. Where the tool supports it, feed the first successful image back in as a style reference for the next one, or reuse a seed value, so the model is extending a known-good layout instead of guessing again from scratch each time.

A before-and-after prompt

Weak prompt: "Make a poster for our fall sale with a discount message."

Strengthened prompt: "A minimalist retail poster, warm autumn color palette (burnt orange, cream). Large bold sans-serif headline text that says "FALL SALE — 30% OFF" centered near the top. Smaller text below it that says "THIS WEEKEND ONLY" in the same font family, lighter weight. No other text. Clean layout, plenty of negative space, no clutter."

The second version fixes the wording in quotes, keeps the total text short, names the font style, and tells the model explicitly not to add anything else — which is usually where an unprompted image adds a stray line of garbled filler text nobody asked for.

When to still finish it by hand

Even with all of this, treat AI-rendered text as a strong first draft rather than a final file for anything that has to be pixel-perfect — a printed sign, packaging that's going to a manufacturer, or a legal disclaimer. Generate the composition and headline with the model, then drop into a design tool for any text that absolutely cannot have a typo. For social graphics, drafts, and internal decks, current models are accurate enough that a clean prompt is often the whole job.

If you want a starting point instead of writing this structure from scratch, the Prompt Library has ready-made prompts for social graphics and marketing visuals you can adapt with your own exact wording and brand colors.