OpenAI's latest image model — near-perfect text rendering, true-to-life colors, 4K native resolution. Photorealistic output, ready to use.
Key improvements in text rendering, color accuracy, speed, and layout flexibility
Text accuracy jumps from ~90–95% to ~99%+. Signs, labels, UI elements, code snippets, and even handwritten notes render cleanly and legibly.
Delivers natural, neutral color rendering without the warm cast and manual cleanup common in older image pipelines.
Rebuilt from the ground up with single-pass inference instead of a two-stage process. Not based on the GPT-4o pipeline anymore — faster and higher quality.
Generated portraits described as 'indistinguishable from real photographs.' Accurate hand anatomy and realistic reflections.
Generates IKEA storefronts, YouTube interfaces, Minecraft scenes, and world maps with surprising geographic accuracy.
Adds 16:9, 9:16, and more beyond legacy square-first layouts. Better for presentations, social creatives, and video content.
See how GPT Image 2 performs in real-world scenarios — brand campaigns, e-commerce photography, multilingual design, and more

Precise text rendering + photographic composition. Generate campaign-ready visuals with product labels, slogans, and CTA text in one shot.
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Material details, lighting quality, product labels — generate museum-grade still photography without a physical studio, drastically reducing production costs.
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Chinese, Japanese, Korean, Arabic — CJK and multi-script text rendering is accurate and clear. Global-market visual content in one step.
Start CreatingBased on real-world usage, compared against current mainstream image generation models
Three steps to start creating
Describe the image you want in the input box above, then select a model and aspect ratio. The more specific your prompt, the better the result.
Click Generate and GPT Image 2 will produce a high-quality image in seconds. Not satisfied? Tweak your prompt and try again.
Happy with the result? Download directly. You can also upload reference images for further editing — keep refining until it's perfect.
From brand marketing to product design — where GPT Image 2 shines
Near-perfect text rendering means product labels, headlines, and call-to-action text will finally be usable straight out of the generator.
No more manual text fixesGenerate realistic app interfaces, dashboards, and website screenshots with legible interface text and proper layout.
Pixel-accurate UI previewsExcellent non-Latin script support opens AI image generation to Chinese, Arabic, Japanese, and other language markets.
Global content at scaleTrue-to-life color rendering and photorealism make AI-generated images viable for product catalogs and editorial use.
Studio quality without a studioFrom hero visuals to extended materials — maintain consistent brand colors, fonts, and visual style across an entire campaign.
Brand visual consistency guaranteedGenerate visuals tailored to each platform's size requirements (Instagram, Xiaohongshu, WeChat) — batch-create assets for every channel.
One-click multi-channel sizingMaster these 6 techniques to get the most out of GPT Image 2
Begin with the overall scene: what's the subject, where is it, what's the lighting. A clear scene setup is the foundation of great output.
Wrap text you want rendered in quotes and specify font style or position. Example: "Large headline at the top reading 'SALE'".
Specify material textures: matte metal, smooth glass, rough stone… the more specific, the more realistic the result.
Choose ratio based on use case: 1:1 for e-commerce covers, 16:9 for social media landscape, 9:16 for phone wallpapers.
Uploading a reference image helps convey style, tone, or composition intent far more effectively than text alone.
When creating multiple images in a series, establish consistent visual keywords (color palette, composition, style) before generating each one.
Real feedback from developers, designers, and creators using GPT Image 2.
Users report text on signs, product labels, code snippets, and even handwritten notes renders cleanly — described as 'finally usable for production work.'
The warm yellow tint that plagued GPT Image 1.5 is gone. Images show natural, neutral color rendering without post-processing.
Metadata analysis and inference patterns confirm a completely new model — not built on the GPT-4o pipeline. Single-pass inference delivers faster generation.
Pieter Levels spotted three anonymous models on LM Arena under code names maskingtape, gaffertape, and packingtape. 3.7K likes.
Blake Robbins shares early examples from the Arena tests. Community confirms multiple code-named models. 2.8K likes.
Min Choi reacts to the model quality, calling it a significant leap over GPT Image 1.5. 776 likes.
Mark Kretschmann highlights the text rendering accuracy breakthrough across multiple test cases. 423 likes.
Angel (@Angaisb_) is among the first to document the anonymous tape-named models appearing on LM Arena. 435 likes.
Mark Kretschmann shares an extensive gallery of outputs, demonstrating world knowledge and photorealism capabilities.
4K resolution, 99%+ text accuracy, 11+ aspect ratios — start creating now