MODEL GUIDE · POSITIONING & PRICING · UPDATED 2026-08-28

GPT Image 2: Positioning, Features, and Pricing

GPT Image 2 is OpenAI’s most capable image generation and editing model, aimed at production work that needs stronger image quality, typography, structured composition, and high-fidelity edits. This guide focuses on the model itself—what it does well, what it costs, and when to choose it.

Positioning: where does it fit?

OpenAI uses “ChatGPT Images 2.0” for the consumer experience and `gpt-image-2` for the API model. Informal names such as ChatGPT Image 2 usually refer to the same generation, but official names are clearer in documentation.

Position: OpenAI flagship image model · Focus: high-quality generation + high-fidelity editing · Released: 2026-04-21

What is GPT Image 2?

GPT Image 2 is OpenAI’s flagship model for image generation and editing. Its official model page describes it as a state-of-the-art model for fast, high-quality generation and editing, with text input, image input and output, flexible sizes, and high-fidelity references.

Model

gpt-image-2

Official position

The recommended default for new work when image quality, editing reliability, and fewer retries matter.

Best suited to

Photorealism, text-heavy design, complex composition, compositing, and identity-sensitive edits.

Quality

low · medium · high · auto

Output formats

PNG · JPEG · WebP

Snapshot

gpt-image-2-2026-04-21

What does the official prompting guide say it does well?

1. More reliable text and layout

OpenAI’s prompting guide highlights crisp lettering, consistent layouts, and strong contrast. This makes the model useful for posters, infographics, menus, packaging, and explainers. The guide recommends high quality for dense text or complex layouts.

2. Stronger structured visuals

The model must understand not only what to draw but how elements relate. Official guidance specifically calls out infographics, diagrams, multi-panel compositions, and labeled visuals, allowing prompts to define count, placement, reading order, negative space, and text zones.

3. High-fidelity image editing

GPT Image 2 automatically processes image inputs at high fidelity. It is suited to identity-preserving edits, environment replacement, relighting, product-background changes, combining product references, and style transformation while retaining core structure. Reference images add input-token cost.

4. Style control and real-world knowledge

The official guide emphasizes precise style control, style transfer, and real-world knowledge. For products, architecture, vehicles, environments, and scenes with physical relationships, the model aims to preserve both visual direction and plausible relationships.

Supported image sizes

GPT Image 2 supports thousands of valid resolutions. Popular examples include:

1024×1024 · 1536×1024 · 1024×1536 · 2048×2048 · 2048×1152 · 3840×2160 · 2160×3840

Maximum edge length is 3840px.
Both edges must be multiples of 16px.
The long-to-short edge ratio cannot exceed 3:1.
Total pixels must be between 655,360 and 8,294,400.

Square images are typically fastest. Use low for drafts and thumbnails, then move to medium or high for final posters and dense text.

How much does the GPT Image 2 API cost?

The API is token-priced. Total cost combines prompt text, reference-image input, and generated-image output. Current standard rates are:

Modality	Input	Cached input	Output
Image tokens	$8 / 1M	$2 / 1M	$30 / 1M
Text tokens	$5 / 1M	$1.25 / 1M	—

The official calculator gives these output-only estimates for common sizes, excluding prompt and reference-image input:

Size	Low	Medium	High
1024×1024	$0.006	$0.053	$0.211
1024×1536	$0.005	$0.041	$0.165
1536×1024	$0.005	$0.041	$0.165

Low

Best for drafts, batch exploration, and latency-sensitive work. Confirm direction before increasing quality.

Medium

A balanced choice for most final illustrations, social visuals, and standard product images.

High

Best for dense text, complex layouts, realistic materials, and delivery assets. Reserve it for detail-critical work.

Price should not be judged by one render alone. If low quality requires repeated retries while medium produces a usable result once, medium may cost less in practice. Official guidance also highlights fewer retries as a reason to choose GPT Image 2.

Best use cases

Posters with headlines, labels, or explanatory text.
Infographics, process diagrams, explainers, and multi-panel content.
Product photography, ecommerce hero images, and multi-reference product compositions.
Edits that preserve the identity of a person, product, or building.
Brand visuals, UI concepts, and designs that benefit from iterative conversation.

How to prompt GPT Image 2 reliably

GPT Image 2 responds well to clear natural-language instructions rather than unordered style tags. The site’s universal formula remains useful:

[purpose] + [subject] + [action or state] + [environment] + [composition and camera] + [lighting] + [color] + [style or medium] + [details] + [constraints]

For editing, specify what must remain, what alone should change, and what must not change. For in-image text, provide the exact copy plus language, placement, hierarchy, alignment, and contrast.

Same scene: detailed prompt vs concise prompt

Both images use the same model, 16:9 ratio, and subject. The detailed version specifies composition, lighting, materials, and constraints; the concise version retains only the directions most likely to change the image.

View detailed prompt

Create a cinematic travel poster for a high-end editorial feature, with generous clean negative space on the left for a headline and a short introduction. An adult East Asian woman with natural facial features, dark eyes, and long black hair wears an ivory linen maxi dress and a wide-brimmed straw hat. She walks barefoot through shallow seawater, gently lifting one side of her dress and naturally looking back toward the camera. The scene takes place on a black volcanic beach at sunset, with steep coastal cliffs, rolling waves, and distant islands partially covered by delicate sea mist. Use a strict 16:9 horizontal full-body wide shot at eye level. Position the woman on the right third of the frame, leaving a large uncluttered area on the left. Let the coastline extend diagonally from the lower left toward the upper right, creating a natural leading line and emphasizing the width and depth of the landscape. The setting sun shines through thin clouds behind the woman, creating a soft golden rim light around her silhouette. Long, subtle reflections stretch across the wet sand and shallow water. Use a restrained palette of deep ocean blue, volcanic black, warm ivory, and golden amber, accented with small amounts of desaturated teal. High-end photorealistic cinematic photography with the visual quality of a luxury travel magazine, independent film poster, and fine-art photography exhibition. Show realistic linen fabric texture, the dress moving gently in the sea breeze, footprints in wet sand, shallow water surrounding her ankles, delicate atmospheric mist, suspended droplets, and natural skin and hair texture. Maintain authentic and natural East Asian facial characteristics without exaggeration or stereotyping. Preserve realistic body proportions and anatomically correct hands and feet. No additional people, boats, buildings, decorative text, logos, or watermarks. Avoid excessive HDR, oversaturated or fluorescent colors, heavy filters, artificial skin smoothing, exaggerated poses, plastic CGI texture, cartoon styling, or overly Westernized facial features.

View concise prompt

Create a high-end cinematic travel photograph in a 16:9 horizontal composition. An adult East Asian woman with natural facial features, wearing an ivory linen maxi dress and a wide-brimmed straw hat, walks barefoot through shallow water on a black volcanic beach at sunset. She gently lifts her dress and looks back toward the camera. Place her on the right third of the frame and leave generous clean negative space on the left. Include distant cliffs, rolling waves, islands, and soft sea mist. Use golden backlighting, realistic reflections, deep ocean blue, volcanic black, warm ivory, and amber tones. Photorealistic luxury travel magazine style with natural skin, realistic fabric and anatomically correct hands and feet. No additional people, text, logos, watermark, artificial skin smoothing, excessive HDR, or CGI appearance.

GPT Image 2Ratio: 16:9 · Subject: East Asian woman · Scene: volcanic beach at sunset

GPT Image 2 detailed travel prompt result with an East Asian woman walking on a volcanic beach at sunset — **Detailed prompt**More editorially controlled: stable right-side placement, cleaner left-side space, and clearer direction for the coastline, rim light, and fabric.

GPT Image 2 concise travel prompt result with an East Asian woman walking on a volcanic beach at sunset — **Concise prompt**More direct and still accurate in subject and mood, but the sunset and cliffs occupy more of the left side, reducing clean headline space.

Comparison takeaway

Longer is not automatically better. Use the detailed version when copy space, subject placement, or lighting must remain controlled; use the concise version for fast exploration. Start with the core directions, then add detail only for variables that truly need control.

Limitations and considerations

Complex images can still contain text, count, or local-detail errors and require review.
High resolution and high quality increase cost and latency.
Reference edits automatically use high-fidelity input and can consume more image-input tokens.
Prompts and outputs are subject to OpenAI content policies and safety filtering.

Conclusion: where GPT Image 2 stands out

GPT Image 2 is not positioned as the lowest-cost batch model. It is the flagship choice for final quality, typography and layout, high-fidelity editing, and fewer retries. Use low to validate direction, medium for most final work, and high for dense text, complex layouts, and delivery assets.

Official OpenAI sources

FAQ

Are GPT Image 2 and ChatGPT Images 2.0 the same?

They refer to the same generation of image capability in different contexts: ChatGPT Images 2.0 is the product name, while `gpt-image-2` is the API model name.

Does GPT Image 2 support editing?

Yes. It supports full-image edits, masked local edits, and multiple reference images.

Should I use low, medium, or high quality?

Use low for drafts, medium for normal final visuals, and high for dense text, complex layouts, or delivery assets.