Native 2K, 4K Available
Standard output at 2K, with 4K on hand for print and large crops.
GPT Image 2 AI Image Generator
OpenAI's GPT Image 2.0 reads a hundred-word brief and attempts all of it, with independent quality and resolution controls from 1K to 4K.
- GPT Image 2
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Write the Whole Brief and Have It Honoured
GPT Image 2 is OpenAI's image model, and its defining behaviour is that a long instruction does not get averaged into a general impression.
Most models degrade as a brief gets longer. Add a fifth requirement and the second one quietly disappears; specify eight objects and you get six. GPT Image 2 was built to hold multi-part constraints together, with OpenAI quoting instruction-following accuracy at around 98 percent, and it renders text at close to character-level precision rather than approximating letterforms.
Use GPT Image 2 when the picture has requirements rather than a vibe. Build regulated packaging comps, spec-driven product imagery, annotated layouts, multi-object still lifes, and anything where a reviewer will check the output against a list.
What Is GPT Image 2.0?
GPT Image 2 is an AI image generation model developed by OpenAI, the successor to GPT Image 1.5 and GPT Image 1 and the model behind image generation in ChatGPT. Virse exposes it directly, with the quality and resolution controls the chat interface keeps hidden.
The model is built around three major strengths:
- Multi-constraint instruction following, quoted at roughly 98 percent accuracy
- Text rendering at near character-level precision
- Independent quality and resolution controls in a single model
GPT Image 2 runs on an autoregressive architecture rather than the diffusion approach most of its peers use, which OpenAI credits for generation three to five times faster than the previous version. Native output is 2K with 4K available, aspect ratios run from 3:1 to 1:3, and rendering quality is selectable at Low, Medium, or High independently of size.
GPT Image 2 Specs at a Glance
Three Quality Grades
Low, Medium, and High, chosen separately from output size.
Four Output Sizes
1K, 2K, 3K, and 4K, each available at every quality grade.
~98% Instruction Following
Multi-part briefs come back with the parts intact.
Aspect Ratios 3:1 to 1:3
Wide panoramas through tall verticals from the same brief.
Autoregressive Architecture
A different generation approach from diffusion, credited with a 3–5x speed gain.
Key Features of the GPT Image 2 AI Image Generator
Long Briefs Are Worth Writing
Because the model holds many constraints at once, detail you write is detail you get. A hundred-word specification is not wasted effort here the way it is on models that summarise your intent before generating.
Quality and Size Move Independently
Two controls rather than one means a large draft and a small final are both possible. Most models tie fidelity to output size and leave you no way to separate them.
Near Character-Level Text
Headlines, labels, and signage come back readable rather than approximated, which puts this among the strongest models here for images that contain words.
Coherent Multi-Object Scenes
Compositions where several objects must relate correctly — sitting on surfaces, casting matching shadows, sharing one light direction — hold together rather than drifting into physical nonsense.
Reference Image Input
Supply pictures alongside the prompt and the model works from them, preserving what you name and changing what you ask for.
World Knowledge From the GPT Family
The model draws on the same underlying knowledge as its text siblings, which shows in how it handles real objects, contexts, and conventions without being described from scratch.
Build with GPT Image 2 in Virse
Briefs with fixed requirements rarely arrive finished. They get assembled from a spec sheet, a brand guide, a reference photo, and three rounds of feedback. Virse keeps that material next to the output. The brief, the references it came from, and every generation against it stay on one canvas, so checking a result against its requirements does not mean opening a second window.
Keep the Spec Beside the Render
Park the requirement list on the canvas next to the image so review happens against the source rather than from memory.
Draft Low, Deliver High
Settle composition at the Low grade, then re-run the identical brief at Medium or High once the content is agreed.
Access 30+ Creative Models
Move between GPT Image 2 and 30+ other image and video models without leaving the canvas or rewriting the brief.
Version a Brief as It Changes
Each round of feedback produces a new generation beside the last, so the trail from first draft to approved asset stays intact.
What Can You Create with GPT Image 2?
Spec-Driven Product Imagery
Renders that must match a written specification down to arrangement and finish.
Packaging and Label Comps
Front-of-pack layouts carrying exact product names, descriptors, and legally required copy.
Annotated Diagrams
Cross-sections and explanatory graphics whose labels have to be correct, not decorative.
Multi-Object Still Life
Arrangements where each item's position, scale, and shadow are specified.
Interior and Architectural Views
Spaces built to a described plan rather than an approximate mood.
Editorial Illustration
Concept imagery for articles where the brief carries several ideas at once.
How to Use GPT Image 2 in Virse
Set Quality to Low
Start at the lowest grade while you are still deciding what the picture should contain.
Write the Full Specification
List every element, its position, and anything that must be exactly so. Length is an advantage here.
Check the Output Against Your List
Compare item by item rather than by overall impression, then add the clause for anything missing.
Re-Run at the Delivery Setting
Take the working brief up to Medium or High at your target size, unchanged.
How to Write a GPT Image 2 Prompt
A useful GPT Image 2 prompt usually includes five elements:
- Every Object
- Its Position
- Lighting
- Camera
- On-Image Text
Alih-alih menulis
A cozy reading nook, warm and inviting, beautiful natural light.
Tulis
A window seat built into a bay window, upholstered in faded green velvet, with three mismatched cushions pushed against the left side. A hardback book lies open face-down on the seat. Late afternoon sun enters from the right at a low angle, casting the window frame's shadow across the cushions. Beyond the glass, an out-of-focus garden. Shot straight on from two metres back, the seat filling the lower two-thirds of the frame.
GPT Image 2 Prompt Examples
Interior Built to Spec
A narrow galley kitchen photographed from the doorway, straight on, at eye level. Cabinets in matte sage green with brass cup handles along the left wall. Open shelving on the right holding six white ceramic bowls in a single row. A window at the far end with the blind halfway down. Overcast daylight from the window only, no artificial light, soft shadows. The floor is unglazed terracotta tile laid in a running bond pattern.
Multi-Object Still Life
Four objects arranged on a weathered oak table, photographed from 45 degrees above. A pewter jug at the back left, a folded grey linen cloth in front of it, three walnuts scattered to the right of the cloth, and a single pear at the front right corner. Each object casts a shadow consistent with one light source from the upper left. The walnuts sit slightly apart, none touching. Muted palette, restrained contrast, visible wood grain running left to right.
Label Comp With Exact Copy
A rectangular jar of preserves photographed straight on against a plain cream background. The front label reads ORCHARD ROW in a narrow serif across the top third, with "Damson & Bay Leaf" beneath it in italic at half the size, and "227g" in small caps at the bottom edge. Warm even light from the front left, one soft shadow to the right of the jar. Label occupies the middle 60 percent of the jar's height, with equal margins either side.
GPT Image 2 vs. GPT Image 1.5 and GPT Image 1
| Dimensi | GPT Image 1 | GPT Image 1.5 | GPT Image 2 |
|---|---|---|---|
| Quality control | None | None | Low / Medium / High |
| Resolution control | None | None | 1K / 2K / 3K / 4K |
| Architecture | Diffusion-era | Diffusion-era | Autoregressive |
| Generation speed | Baseline | Baseline | 3–5x faster than predecessor |
| Text rendering | Approximate | Improved | Near character-level |
| Still worth using for | Matching an existing asset set | Matching an existing asset set | All new work |
Tips for Better GPT Image 2 Results
Write More Than Feels Necessary
This is the rare model where a longer brief returns a better image. Detail you leave out is detail the model chooses for you.
Name Positions, Not Just Objects
"A jug at the back left" is actionable. "A jug" leaves placement to chance, and placement is usually what the review comments are about.
Type Out Any Text Verbatim
Words that should appear in the image have to appear in the prompt. Described text becomes invented text.
Keep Quality and Size Separate in Your Head
Quality changes how well the picture is rendered; size changes how large it is. Changing both at once makes it impossible to tell which produced the difference.
GPT Image 2 FAQ
What is GPT Image 2.0?
GPT Image 2 is OpenAI's image generation model, successor to GPT Image 1.5 and GPT Image 1. It offers independent quality settings and resolutions from 1K to 4K, with native output at 2K.
Can GPT Image 2 generate 4K images?
Yes, at every quality grade. Native output is 2K, with 4K available for print and heavy crops.
Is GPT Image 2 free, and what does it cost?
GPT Image 2 is available on Virse's paid plans. Generation draws on a monthly credit allowance rather than a charge per image, and the higher plans make it unmetered within fair use. Current plan rates are listed on the Virse pricing page.
What is the difference between the Low, Medium, and High settings?
They control rendering fidelity, not content. The same prompt produces the same picture at each grade; High resolves fine detail, texture, and edges that Low leaves soft.
How is GPT Image 2 different from GPT Image 1.5?
GPT Image 2 is newer, runs on an autoregressive architecture, generates three to five times faster, and adds quality and resolution controls the earlier versions do not have.
Can GPT Image 2 render text inside an image?
Yes, at close to character-level precision. Type the exact words in the prompt rather than describing that text should be present.
Can GPT Image 2 work from a reference image?
Yes. Supply pictures alongside the written brief and the model generates from them as well as from the text.
How do I use GPT Image 2 in Virse?
Select it from the model list, choose a size and a quality grade, write your brief, and generate. Start at the Low grade while the content is still being decided.
Specify It, Then Check It Off
Write the requirement list, hand the whole thing over, and review the result against the list rather than against a feeling.