GPT Image 2.5 vs Flux 3 for AI text — posters, packaging, signs

The moment an image has to say something, the shortlist gets short. On eroq, the main models positioned for in-image text are GPT Image 2.5 Sunburst from OpenAI, the sharpest at lettering in the lineup; its sibling GPT Image 2.5 Flare, with the same text skills under a more dramatic rendering; and Flux 3 Image from Black Forest Labs, with reliable typography inside natural, photoreal light. The one-line answer is that where the words live decides the model. Words that are the layout go to Sunburst. Words printed on something inside a photograph go to Flux 3. A single title over a dramatic image goes to Flare.

The numbers

	Sunburst	Flare	Flux 3 Image
Maker	OpenAI	OpenAI	Black Forest Labs
Price per image	31 credits / image	31 credits / image	32 credits / image
Typical render	about 15 seconds	about 15 seconds	about 20 seconds
Text strength	sharpest in the lineup	strong, for short titles	reliable, inside photoreal scenes

Text costs nothing extra: an image is an image, at every format. The real cost of text is the re-roll. A take with a misspelled word is still a successful render and is billed like one, so budget a batch for text-critical work: four takes cost 124 credits on Sunburst and 128 credits on Flux 3. A render that actually fails refunds automatically.

One more option exists for when the text and the highest fidelity both matter: Nano Banana Pro, positioned for the most accurate text of Google's line, at 124 credits / image, the priciest image model on eroq.

None of them reads pictures on eroq, all are open to every account, and each is moderated upstream by its provider (a declined prompt is never billed).

Where the words live decides the model

Text as layout. A typographic poster, a menu, an app screen, a label design shown flat. The words are the design, and the picture is built around their position and hierarchy. That is Sunburst's job.

Text as an object. A hand-painted shop sign, a label on a bottle on a table, neon across a wet street. The words belong to a thing inside a photographed scene, and the light on that thing has to be believable. That is Flux 3's job.

Text as a title over atmosphere. A film poster, an album cover, a game key art title. One short line, and an image that has to hit hard. That is Flare's job.

Posters

Typographic posters with a hierarchy (a headline over a date line) start on Sunburst, with the grid described in plain words. A film or album poster carrying one title gets more from Flare's drama than from Sunburst's restraint. A photographic poster, a real-looking scene with a short headline, stays honest on Flux 3. The AI movie poster walkthrough takes one from prompt to animated clip.

Packaging and labels

Sunburst suits packaging shown as design: front-facing boxes, a lineup of tins with identical labels, a label layout presented flat in studio light. Flux 3 suits packaging shown as life: the bottle on the breakfast table, the bag on a café counter, morning light across the label.

Neither model reproduces your existing packaging: they read no pictures on eroq and render your words onto a product they invent. For a real product that must match its photos, Eroq One reads up to ten references.

Signs and environmental text

Flux 3 is the pick for text that sits in the world: shopfronts, street signs, a mural, neon in the rain. Sunburst suits designed signage shown as a mockup: airport wayfinding, an exhibition wall, an event banner seen straight on.

How to prompt text that reads

The rules hold on Sunburst, Flare and Flux 3 alike:

1. Put the exact words in double quotes. the sign reads "OPEN LATE" tells the model these are letters to render, not part of the scene.
2. Keep each piece of text short. A few words per element. Full sentences and blocks of body copy are where lettering breaks first.
3. Say where the text sits and what it is on. "Across the top", "on the bottle's paper label", "painted on the brick above the door".
4. Describe the type instead of naming a font. "Bold condensed sans", "thin elegant serif", "hand-painted script", "chunky slab serif".
5. Give the words room. Ask for a plain area or "generous empty space above the subject" so the text is not fighting a busy background.
6. Keep the count low. One or two text elements is the safe zone; when there are two, name the hierarchy: "a large headline" and "a small line beneath it".
7. Proofread every take. Run two to four, keep the clean one. If a word keeps failing, shorten it, swap it for a simpler one, or leave the space empty and set the type later in your design tool.

The longer version is in how to get legible text in AI images.

What still fails

Long paragraphs of small text, many separate text blocks, a specific brand font or a real logo, and tiny lettering wrapped around a curved surface are the hard cases. With no Edit mode on these models, a wrong letter cannot be patched in place: re-roll, or fix the word in your design tool.

Ready-made prompts are in 26 GPT Image 2.5 prompts and Flux 3 typography prompts. Or open the image studio and test one of the six below.

Example prompts

Sunburst, a typographic poster. A grid, a hierarchy and a date: words as layout.

A Swiss-style typographic poster for a jazz festival, off-white background, a large red circle in the upper right, the headline "BLUE NOTE WEEK" in heavy black sans-serif across the left side, "12 TO 14 JUNE" in small type beneath it, strict grid, generous margins, print design.

Flux 3, neon in a photographed street. The sign is an object lit by its own glow and by the rain.

A tiny noodle bar on a rainy side street at night, a red neon sign in the window reading "OPEN LATE", steam fogging the glass, a cook visible behind the counter, reflections on the wet asphalt, 35mm photograph.

Sunburst, packaging as design. One label repeated cleanly across a lineup.

Three tins of loose-leaf tea in a row on a pale sage background, front-facing, each tin a different pastel colour, each label reading "NORDIC LEAF" in clean white sans-serif with a small pine icon, soft even studio light, packaging design presentation.

Flux 3, a label in daylight. The product lives on a table, not in a studio.

A bottle of olive oil on a rustic kitchen table beside a loaf of sourdough, morning light from a window, the paper label reading "CASA VERDE" in dark green serif, crumbs and a bread knife on the board, lifestyle product photograph.

Flare, a title over drama. One line of text, everything else atmosphere.

A science-fiction film poster: an astronaut standing on a frozen sea beneath a giant ringed planet, cold blue light with a warm rim on the visor, ice crystals hanging in the air, the title "COLD ORBIT" in wide-spaced capitals at the bottom.

Sunburst, a signage mockup. Designed signage, seen straight on.

A wayfinding sign in a modern airport terminal, a dark grey panel hanging from the ceiling, a white arrow beside the word "GATES" and a second arrow beside "BAGGAGE", clean sans-serif lettering, soft ambient daylight, architectural photograph.

FAQ

Which AI image model is best for text on eroq?

On eroq, GPT Image 2.5 Sunburst is the model positioned as best at lettering. Flux 3 Image is the pick when the text sits inside a photoreal scene, and Nano Banana Pro is the accurate but pricier option.

How do I stop AI images from misspelling words?

Quote the exact words, keep each text element short, limit the image to one or two of them, and run a few takes. Keep the clean take; if a word keeps breaking, shorten or simplify it.

Does text in an image cost more credits?

No. Every model charges the same per image whatever is in it. Misspelled takes are billed like any other successful render, which is why text work deserves a small batch.

Can I use my brand's font or logo?

Not from a file: these models only read the prompt. Describe the type style you want, and place exact brand fonts and logos in your design tool afterwards.