The best AI image generator for text in 2026 is GPT Image 2.5 (or GPT Image 2) when the words must be exactly right, Ideogram v4 for typographic posters and social graphics, and Recraft V4.1 for logos and brand layouts. Qwen Image 3.0 is the strongest budget pick, especially for Chinese text. No model is perfect, so keep the text short, put it in quotes, and fix stray letters with an edit instead of re-rolling the whole image.
This comparison was written as of 20 October 2026. Every price below is the credit cost in Kenerate AI's own model config on that date, and every feature claim about a model comes from the vendor's documentation or an independent source linked at the end.
Which AI image generator is best for text right now?
Text inside images used to be the giveaway of an AI picture: "COFEE SHPO" on a storefront, menus in alien script. That changed over the last two years. Several models now spell short headlines reliably, and a few can lay out a full poster. Reviewers still disagree on a single winner. Zapier's roundup (updated April 2026) names Ideogram as the tool that "has cracked" text, while other reviews favour OpenAI's GPT Image 2 for multilingual text.
The honest answer is that the best model depends on what kind of text you need:
| Model (on Kenerate) | Best for | References | Resolution | Credits per image (as of 20 Oct 2026) |
|---|---|---|---|---|
| GPT Image 2.5 Sunburst | Exact wording, dense layouts, menus, UI mockups | Up to 16 | 1K–4K, 5 quality tiers | 7.2 at medium 1K · 27 at high 1K · 3 at low 1K |
| GPT Image 2.5 Flare | Fast drafts of text-heavy images | Up to 16 | 1K–4K, 5 quality tiers | Same table as Sunburst (7.2 at medium 1K) |
| GPT Image 2 | Maximum realism with signs and labels | Up to 16 | 1K / 2K / 4K | 18 at medium 1K |
| Ideogram v4 | Posters, quotes, social graphics | None (text-to-image only) | 5 aspect ratios | 15 |
| Recraft V4.1 | Logos, brand layouts, typography as design | None | 1:1 and other ratios | 12 (Flash 2.4 · Pro 75) |
| Qwen Image 3.0 | Cheap volume, Chinese + English text | Up to 3 (edits) | 1K or 2K, same price | 9 (+0.9 per edit reference) |
| Seedream 5.0 Pro | Illustrated posters, anime titles | Up to 10 | 1K / 1.5K / 2K | 13.5 at 1K–1.5K · 27 at 2K |
| Nano Banana 2.1 | Product shots with labels, same product across shots | Up to 14 | 1K / 2K / 4K | 21 at 1K · 31.5 at 2K · 42 at 4K |
New Kenerate accounts get 25 free credits. On the free plan, Qwen Image 3.0 is the model in this table you can use, so that's two free test images at 9 credits each in the image studio. GPT Image 2.5, GPT Image 2, Ideogram v4, Recraft V4.1 (including Flash), Seedream 5.0 Pro and Nano Banana 2.1 unlock with a credit pack, from $15 for 1,300 credits.
Why do AI image generators get text wrong?
Diffusion models don't read and write characters the way a word processor does. They learn what words look like as shapes in millions of training images, then paint those shapes back. A common word in a big font ("SALE", "OPEN") appears so often that the model has a strong picture of it. A rare brand name, a long sentence or small print gives it much less to work from, so letters get swapped, doubled or invented. Zapier's guide puts it simply: most generators still struggle because diffusion "doesn't lend itself" to precise lettering.
Three things make errors more likely:
- Length. Every extra word is another chance for a mistake, which is why prompt guides for text-focused models keep recommending short text.
- Small size. Fine print on a label or a menu price list is where letters melt first.
- Perspective and texture. Text on a curved mug, a neon tube or a wet window is harder than flat text on a poster.
Newer models close the gap with better text encoders and training data built for typography. Alibaba's Qwen-Image technical report, for example, describes a dedicated data pipeline for text rendering and evaluates English and Chinese text as separate tasks.
Which model should you pick for each job?
What is the best AI for posters and flyers with text?
For a headline plus one or two supporting lines, Ideogram v4 and GPT Image 2.5 are the safest bets. Ideogram leans toward bold graphic design and handles big display type well. GPT Image 2.5 follows long, detailed layout instructions ("headline at the top, date and venue in the bottom third, small sponsor line") more literally. If the poster is illustrated or anime-styled, Seedream 5.0 Pro often gives the nicer artwork, with a short title.
Try it on the AI poster generator, which runs the same models with poster-ready presets.
What is the best AI for logos with text?
Recraft V4.1 is built for this. Recraft describes V4 as treating typography as part of the layout rather than an overlay, which suits wordmarks and badges. One caution from independent documentation (Pletor's Recraft V4 model notes): dense, integrated text such as packaging copy can look right while the actual words are wrong, so check every letter. For a short brand name it is a strong first choice; Recraft V4.1 Flash at 2.4 credits is a cheap way to explore dozens of logo directions first. More logo prompts are on the AI logo generator page and the Recraft model page.
What is the best AI for menus, infographics and long text?
Long text is where GPT Image 2.5 Sunburst at high quality pulls ahead. It spends longer per image on fine detail, and it accepts up to 16 reference images, so you can hand it a rough layout or a brand style sheet. Expect to proofread: even the best model can slip on the 40th word. Our GPT Image 2.5 guide covers the Flare vs Sunburst trade-off in detail.
What is the best AI for text in Chinese or other languages?
Qwen Image 3.0 accepts English and Chinese prompts, and the Qwen-Image line is known for complex Chinese text. On Kenerate it costs 9 credits at either 1K or 2K, which makes it the cheapest serious option in this list. GPT Image 2 is the other strong choice for non-Latin scripts. We compared the two head-to-head in Qwen Image 3 vs GPT Image 2.
What is the best AI for product labels and packaging?
When the product already exists, use a reference-based model. Nano Banana 2.1 takes up to 14 references and is described as having cleaner text than the previous version, so you can upload the real packshot and ask for a new scene while keeping the label. GPT Image 2.5 (16 references) is the alternative when the label itself is new and needs exact wording.
How do you prompt an AI image generator for accurate text?
These rules work on every model in the table above:
- Put the exact words in quotation marks. Ideogram's prompt-structure docs recommend the pattern text that reads "[exact words]". Third-party Recraft V4 guides give the same advice, and the convention works on GPT Image and Qwen too.
- Mention the text early in the prompt. It keeps the words from getting lost behind a long scene description.
- Keep each text block short. Aim for one to six words per line. Split a long tagline into a headline and a subline.
- Describe the type, not just the words. "Bold condensed sans-serif in white", "hand-lettered brush script", "serif headline like a book cover". Font style words change the result a lot.
- Say where the text sits. "Centred at the top", "on the shop sign above the door", "bottom left corner, small".
- Use a ratio that gives the text room. A 4:5 or 9:16 poster fits a stacked headline better than a square.
- Avoid asking for text you don't need. Every unrequested label is another chance for gibberish. Add "no other text" at the end.
Here is a prompt that follows all seven rules:
A minimalist concert poster, headline text that reads "NIGHT SHIFT" in huge bold condensed sans-serif at the top, smaller text that reads "LIVE · 14 NOV" centred below it, a neon-lit city street at night in the background, deep blue and orange palette, 4:5, no other text.
How do you fix misspelled text in an AI image?
Re-rolling until the spelling is right wastes credits and loses an image you liked. A targeted edit is cheaper:
- Open the image in the change text in image tool, or upload it as a reference in the image studio.
- Describe only the change: Replace the text "COFEE" on the sign with "COFFEE". Keep the font, colour, size, position and everything else exactly the same.
- Pick an edit model that follows instructions closely. GPT Image 2.5 (edits add 4.5 credits per reference image) and Qwen Image 3.0 (adds 0.9 credits per reference, up to 3) are good fits.
- If one word still fails, fall back to a design tool and set that word by hand. Adobe's own Firefly staff recommend adding text afterwards in Express or Photoshop when wording must be exact.
For print work where every character matters (legal text, prices, phone numbers), the professional workflow is still: generate the image with space for text, then typeset the words in Figma, Canva or Photoshop.
How much does it cost to make text images with AI?
Using Kenerate's credit prices on 20 October 2026, here is what 20 poster drafts would cost on each model at its default (lowest listed) setting:
| Model | Credits per image | 20 drafts |
|---|---|---|
| Recraft V4.1 Flash | 2.4 | 48 |
| GPT Image 2.5 Flare (low, 1K) | 3 | 60 |
| GPT Image 2.5 Flare (medium, 1K) | 7.2 | 144 |
| Qwen Image 3.0 | 9 | 180 |
| Recraft V4.1 | 12 | 240 |
| Seedream 5.0 Pro (1K) | 13.5 | 270 |
| Ideogram v4 | 15 | 300 |
| GPT Image 2 (medium, 1K) | 18 | 360 |
| Nano Banana 2.1 (1K) | 21 | 420 |
A practical way to keep costs down: draft layouts on a cheap model (Recraft V4.1 Flash or GPT Image 2.5 Flare at low quality), pick the composition you like, then re-run that one prompt on a higher tier for the final.
Bottom line
- Exact wording and long text: GPT Image 2.5 Sunburst (high quality) or GPT Image 2.
- Posters and social graphics: Ideogram v4 or GPT Image 2.5.
- Logos and wordmarks: Recraft V4.1, explored first on V4.1 Flash.
- Budget and Chinese text: Qwen Image 3.0.
- Labels on real products: Nano Banana 2.1 with your packshot as a reference.
Whatever you pick, short quoted text, a named font style and a clear position will do more for spelling than switching models. And when one letter goes wrong, edit the word instead of starting over.






