AI image generator with readable text: which Sume models to try
Which Sume image models have a vendor claim about text in images, what each vendor says, and the quality setting Sume's docs suggest for dense text.

For text inside an image, three families in Sume's image catalog have a vendor statement about it: Nano Banana (Google says its Gemini 3 image models render legible, stylized text), FLUX.2 (Black Forest Labs calls [flex] strongest at text and fine detail), and ChatGPT Image 2.5, whose quality tiers Sume's docs point to for dense text. Whether a given model spells your exact string right is a test you run, not a promise.
Vendor statements are from their own pages and Sume's from the Image API docs and Image 1.0, read 2026-09-29.
What do the vendors say?
| Sume id | Vendor statement |
|---|---|
google/nano-banana-pro, google/nano-banana-2 | Google: Gemini 3 image models offer "advanced text rendering" for infographics, menus, diagrams and marketing assets |
black-forest-labs/flux.2-flex, flux.2-pro | Black Forest Labs: the FLUX.2 launch post lists complex typography, infographics, memes and UI mockups with legible fine text, and says [flex] excels at rendering text and fine details |
openai/gpt-image-2.5 | No vendor page read for this post; Sume's Image 1.0 docs say escalate quality for finals, dense text or packaging |
How should I prompt for exact text?
Black Forest Labs' guide says to put the exact string in quotation marks, say where it sits, describe the lettering style and use a hex code for a brand color. The same habits cost nothing on any model.
Which quality setting should I use for dense text?
openai/gpt-image-2.5 takes quality of auto, low, medium, high, xhigh or max, and omitted quality defaults to high. Note that auto reserves max, so an auto request reserves the largest amount. A short label can use a lower tier; a menu or packaging panel may need more.
curl -X POST https://api.sume.com/v1/images \
-H "Authorization: Bearer $SUME_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-image-2.5",
"prompt": "A bakery menu board. Heading: FRESH TODAY. Three lines: Croissant, Baguette, Rye.",
"quality": "high",
"aspect_ratio": "3:4"
}'How do I check the result?
Read every character. Misspellings are the failure that matters, and they show only when you look. Generate a few with n, keep the correct one, and only then move to production sizes.
Sources
Related posts
More in Models
- Does Lyria 3.5 music carry a SynthID watermark?
Google says all Lyria 3.5 audio includes a SynthID watermark. What that means for tracks made through an API, and what Sume's docs do and do not say.
- AI sky replacement: swap the sky and keep the photo
AI sky replacement: send the photo to an image-edit model, describe only the new sky, and list what stays. Then check roof and tree edges. Cost and limits.
- Why AI video models do not lip sync to a voiceover, and what to use
Sume docs: video models do not lip-sync to generated speech or a voice-over. For a talking face use Avatar video or the lip-sync endpoint (still plus audio).
- Batch edit photos with AI: one edit across many photos
To batch edit photos with AI, send the same edit prompt once per photo, with that photo as the reference. How to script it, pace it, and what it costs.
Written by Sume