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GPT Image 2

The model combines advanced multimodal training with diffusion-based image generation. This enables it to convert complex instructions into visually consistent outputs while preserving strong control over composition, typography, and layout.

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Text to Speech

Javascript

Python

                                        const main = async () => {
  const response = await fetch('https://api.ai.cc/v1/images/generations', {
    method: 'POST',
    headers: {
      Authorization: 'Bearer ',
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'openai/gpt-image-2',
      prompt: 'A jellyfish in the ocean',
    }),
  }).then((res) => res.json());

  console.log('Generation:', response);
};

main();

                                        import requests


def main():
    response = requests.post(
        "https://api.ai.cc/v1/images/generations",
        headers={
            "Authorization": "Bearer ",
            "Content-Type": "application/json",
        },
        json={
            "model": "openai/gpt-image-2",
            "prompt": "A jellyfish in the ocean",
        },
    )

    response.raise_for_status()
    data = response.json()

    print("Generation:", data)


if __name__ == "__main__":
    main()

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GPT Image 2

GPT Image 2 (gpt-image-2) is OpenAI's most capable image generation model to date — reason before it draws, search the web in real time, and render production-ready text in over a dozen languages.

What Is GPT Image 2 API?

GPT Image 2 is OpenAI's third-generation flagship image model, officially launched on April 21, 2026. It follows gpt-image-1 (March 2025) and gpt-image-1.5 (December 2025), representing the most significant architectural leap in the series.

What sets GPT Image 2 apart from everything before it is a fundamental shift in how the model approaches generation. Rather than jumping straight from a text prompt to pixels, GPT Image 2 first thinks. It reasons about composition, structure, and accuracy before committing to an output. That reasoning step, borrowed from OpenAI's O-series language models, is what makes it the industry's first truly agentic image generation model.

API Pricing

Image generation:

Input: $10.40 / 1M tokens
Cached input: $2.60 / 1M tokens
Output: $39.00 / 1M tokens

Text input:

Input: $6.50 / 1M tokens
Cached input: $1.625 / 1M tokens

Core Capabilities

GPT Image 2 does not improve any single dimension of image generation — it expands what the category can do. These are the capabilities that matter most for real production workflows.

Agentic Reasoning

Before generating a single pixel, the model researches, plans, and reasons about image structure. This is the first image model with O-series reasoning built in, resulting in fewer failed generations on complex briefs.

Built-In Web Search

GPT Image 2 can query the web in real time before generating, confirming brand logos, event details, product designs, and geographic references that would otherwise be approximated or hallucinated.

Near-Perfect Text Rendering

Typography inside generated images now reads correctly more than 99% of the time. Multi-line headlines, CTA buttons, UI labels, and fine-print captions are all handled reliably, including mixed-script layouts.

2K Resolution & Flexible Aspect Ratios

Outputs up to 2048px, with aspect ratios from 3:1 (ultra-wide banners) to 1:3 (mobile screens). Covers every production format from social ads to presentation slides without post-processing resizing.

GPT Image 2 vs GPT Image 1.5: What Actually Changed?

GPT Image 1.5 was already a capable model for prompt adherence and photorealism. GPT Image 2 adds three fundamentally new capabilities that 1.5 did not have at all: pre-generation reasoning, live web search, and reliable multilingual typography. Additionally, the knowledge cutoff advances from earlier 2025 to December 2025, meaning current brand assets, product designs, and cultural references are rendered accurately without the model defaulting to outdated versions.

Core Differences at a Glance

Feature	GPT Image 1.5	GPT Image 2
Prompt understanding	Good, but often approximate	High precision and context-aware
Text rendering	Frequently distorted or unreadable	Clean, legible, well-placed
Layout handling	Weak structure, inconsistent alignment	Strong layout awareness and hierarchy
Editing workflow	Mostly one-shot generation	Iterative refinement via prompts
Output consistency	Variable across generations	More predictable and stable
Production readiness	Requires post-processing	Closer to ready-to-use outputs

Use Cases

Marketing & Advertising

Produce campaign visuals with accurate headlines, CTAs, and localised copy in a single generation. Web search ensures brand references and product details reflect current assets.

Retail & E-commerce

Generate product imagery at exact platform-required dimensions — square thumbnails, wide banners, and vertical ads — without post-processing. Works with real product names rendered in correct typography.

Infographics & Data Viz

Create visual explainers, chart illustrations, and instructional diagrams where text labels and data values must be legible and accurately placed. Previously near-impossible with AI generation.

UI Mockups & App Design

Generate realistic app screens, interface wireframes, and design system components. The model correctly renders buttons, nav bars, form fields, and iconography with functional-looking layouts.

Storyboarding & Entertainment

Generate 8 coherent storyboard panels from a single scene description. Character consistency across panels makes it viable for pitching and pre-production workflows without frame-by-frame editing.

Education & Training

Build visual learning aids, course diagrams, and instructional posters formatted to exact display requirements. Web search keeps factual visual content accurate and current

GPT Image 2 vs. Competing Image Models

The 2026 AI image landscape is genuinely competitive. GPT Image 2 is not the right tool for every use case, and understanding where it wins and where it doesn't is essential before committing to a workflow.

GPT Image 2Best For: Commercial Production
Text rendering in 10+ scripts
Agentic reasoning + web search
8-image batch consistency
UI mockups and infographics
Deep OpenAI API ecosystem

Midjourney V8

Best For: Artistic Style

Superior aesthetic direction
Editorial and brand campaigns
Precise style reference controls
No public API available
Web interface only

Google Imagen 3

Best For: GCP Ecosystem

Strong photorealism
Native Vertex AI / GCP integration
Excellent landscape and portrait work
Less reliable text rendering
Weaker multi-generation consistency

Flux 2 Pro

Best For: Photorealism at Speed

Exceptional skin textures and realism
Faster generation time
Open-source fine-tuning available
No reasoning or web search
Weaker text handling

Prompting GPT Image 2 Effectively

Working with GPT Image 2 is as much about communication as it is about creativity. Clear, structured prompts tend to produce the best results.

Instead of vague instructions, it helps to define context, composition, and style in a single coherent description. For example, specifying layout structure or visual hierarchy can significantly improve output quality.

Iteration is equally important. Rather than expecting perfection in one pass, refining outputs through follow-up prompts leads to more polished results.

Example Prompt Structure

Element	Description	Example
Context	What the image is for	“Landing page hero section for a SaaS product”
Visual style	Overall aesthetic direction	“Minimalist, modern, soft gradient background”
Composition	Layout and structure	“Centered headline, UI dashboard on the right”
Details	Specific elements	“Include chart widgets and clean typography”
Tone	Emotional or brand feel	“Professional, trustworthy, clean”

Frequently Asked Questions

What makes GPT Image 2 different from other AI image generators?

It focuses on prompt accuracy, structured layouts, and high-quality text rendering, making it more suitable for real-world applications.

How does GPT Image 2 handle text inside images?

‍Text rendering is the headline feature of GPT Image 2. Reported accuracy is above 99%, including full support for CJK characters (Chinese, Japanese, Korean), Hindi, Bengali, and Arabic alongside Latin scripts. Mixed-script layouts — a common requirement for international marketing — are handled natively for the first time in a commercial image model.

Does GPT Image 2 support editing?

Yes, it allows iterative refinement through follow-up prompts, enabling users to improve outputs without starting over.

What is the maximum output resolution?

‍GPT Image 2 outputs up to 2K resolution (2048px) via the API. Support for resolutions above 2K is currently in beta and may produce inconsistent results. Aspect ratios range from 3:1 (ultra-wide) to 1:3 (ultra-tall), covering every standard production format.

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