OpenAIIMAGEGuest engine

GPT Image 2 on VisionX.

OpenAI’s flagship image model, with 1.5 and 1 kept on the roster beneath it.

3models on rosterfrom 2.4 VXper imageup to 16reference imagesCast-readyidentity locked
01

What GPT Image 2 is on the roster

THE MODEL

GPT Image is the OpenAI image lineup on the roster: GPT Image 2 as the flagship, 1.5 as the balanced grade, and the original GPT Image 1 kept available.

Its strength is instruction-following: dense layout briefs, text in image, and precise art direction land more literally than on most models. Reference edits are supported, so it can restyle a Cast frame instead of inventing a stranger.

Takes direction literally

Layout notes, on-image text, and multi-part briefs survive contact with the model.

Reference edits

Feed Cast frames or product shots and ask for the change; identity carries through the edit.

Three grades of spend

The flagship for finals, 1.5 for volume, 1 for looks built on it. VX per image is quoted per grade.

02

What GPT Image 2 actually does

CAPABILITIES

Where the flagship grade separates from 1.5, and why art directors keep routing type-heavy work here.

It reasons about the layout before it draws

GPT Image 2 plans the composition, checks counts and on-image copy, and self-corrects before it finalises. Dense briefs land in one pass more often, which is the whole cost argument for it.

Native reasoning

Type that actually reads

Correctly spelled headlines across scripts and languages — posters, packaging, diagrams and comics survive contact with the model instead of coming back with dream-alphabet lettering.

Text in image

Briefs written like a spec

Exact counts, spatial relationships and multi-element layouts are honoured rather than loosely interpreted. This is the model to route a client mockup to.

Instruction following

The deepest reference budget on the image roster

It takes more reference images per call than any other image route VisionX runs, so a Cast member, a product and a set plate can all condition one frame at once.

Reference edits

Restyle without reinventing

Feed Cast frames or product shots and describe the change. Identity and product geometry carry through the edit rather than being re-imagined.

Conversational editing

Three grades of spend, one family

The flagship for finals, 1.5 for volume, and the original 1 kept available for looks that were built on it. The composer quotes each grade separately before you run.

Cost control
03

Every variant, exactly as the studio runs it

SPEC SHEET

These rows are read live from the engine registry and the pricing engine. What you see here is what the composer quotes.

ModelModesReferencesOutputVX
GPT Image 2GPT Image 2Imageup to 16 refsstills4.2 VX · per image, no references
GPT Image 1.5GPT Image 1.5Imageup to 16 refsstills2.4 VX · per image, no references
GPT Image 1GPT Image 1Imageup to 16 refsstills3.15 VX · per image, no references

Self-serve rates run as low as $0.085 per VX at scale. The composer quotes the exact VX for your shot, references included, before you run it.

04

How to write for GPT Image 2

PROMPTING

GPT Image rewards a brief written like a designer’s spec rather than a mood. Say what goes where, in what order, and quote the copy exactly.

POSTER WITH TITLE TYPE
Film poster. Title reads "Midnight in Tokyo" in condensed serif,
set across two lines, centred in the upper third.

Neon alley at night, rain light, wet asphalt reflections.
Credits block in small caps along the bottom edge.

Use [Image1] as the lead character’s face. Keep wardrobe unchanged.

Quote the copy, character for character

Type that appears in the image should appear in the prompt inside quotation marks. Paraphrased copy comes back paraphrased.

Say where things sit

Upper third, bottom edge, camera left. Spatial instructions are honoured literally, which is exactly why this model is worth its cost on layout work.

Name the count

"Four line icons, numbered one to four" beats "some icons". Counts are one of the things the reasoning pass verifies before it finalises.

Bind the Cast, then describe the change

Attach the reference and ask for the edit rather than re-describing the person. Identity carries through an edit far better than it survives a re-description.

05

What teams route to GPT Image 2

USE CASES

What agencies actually run it for.

Posters and campaign key art

Campaign posters with embedded copy, multilingual signage, and product imagery that depends on accurate typography rather than a lettering pass afterwards.

Storyboards and sequential frames

Consistent characters and locations across a set of frames for ad boards, comics and narrative sequences.

Diagrams, infographics and charts

Text-heavy visuals with structured layouts and legible labels for decks, explainers and educational content.

Packaging concepts

Packaging with accurate brand names, ingredient lists and label copy for concept work and client review.

UI mockups and product screenshots

Interface mockups with readable labels and structured layouts, for early design exploration before anything is built.

Multilingual localisation

The same visual re-run with translated, re-fitted copy for every market in the campaign.

06

GPT Image 2 against the alternatives

COMPARISON

When to route an image brief here instead of to the other flagships on the roster.

GPT Image 2 capability comparison against Seedream 5.0 Pro and Nano Banana Pro
CapabilityGPT Image 2Seedream 5.0 ProNano Banana Pro
Best atType accuracy, literal layoutStylised campaign imageryPhotographic realism
Reference images per callMost on the rosterDeepDeep
On-image textStrongestWorkableWorkable
Cost positionPremiumFlat rate per imagePremium

Qualitative routing guidance, not a benchmark. Exact reference caps and the VX quote for every grade are in the spec sheet above, read live from the registry and the pricing engine.

FAQ

GPT Image 2, answered

What is GPT Image 2 best at?
Work where the type has to be right and the brief has to be followed literally: posters, packaging, diagrams, storyboards and UI mockups. It plans the composition and checks on-image copy before finalising, so dense, text-heavy briefs land in fewer attempts than on models that treat a prompt as a mood.
How is GPT Image 2 different from 1.5?
The flagship adds reasoning before it draws, materially better instruction following, and a stronger hand with on-image text. GPT Image 1.5 stays on the roster as the balanced grade for volume work, and the original GPT Image 1 remains available for looks that were built on it.
Can it generate several consistent images at once?
Yes — a set of frames from one brief can share characters, props and grade. Combined with your VisionX Cast the same face and wardrobe carry across the whole set, and across the other engines on the roster too.
Does GPT Image 2 do reference edits?
Yes, and it takes more reference images per call than any other image route VisionX runs. Feed Cast frames or product shots and describe the change; identity and product geometry carry through the edit instead of being re-invented.
When should I use GPT Image 2 rather than Seedream or Nano Banana?
Choose GPT Image 2 when type accuracy and literal instruction-following matter. Choose Seedream 5.0 Pro for stylised campaign imagery on flat per-image pricing, and Nano Banana Pro when photographic realism is the point. All three read the same Cast, so switching engines never strands a campaign.
Do I need my own OpenAI account?
No. Access, billing and rate limits are handled by VisionX, and the run is quoted and settled against the same VX wallet as every other engine on the roster. Your producers see one invoice.

Try GPT Image 2 on your Cast.

20 VX free on signup, no card required.