GPT Image 2 Explained
GPT Image 2

GPT Image 2 is OpenAI's image generation model, released in April 2026 as the successor to GPT Image 1. Its defining change is that it runs a reasoning pass before generating, working out layout and spatial relationships rather than pattern-matching to a plausible-looking result. GPT Image 2 supports text-to-image generation, reference-image workflows, and mask-based editing, and it is available through the OpenAI API as gpt-image-2 as well as inside ChatGPT.

GPT Image 2 pricing depends on resolution and quality tier. At 1024x1024, a low-quality image is roughly $0.006, medium is around $0.053, and high quality is about $0.211. A 1920x1080 render runs from about $0.005 to $0.158, and a full 3840x2160 image reaches roughly $0.401 at high quality. Token-based API pricing is commonly quoted around $8 per million input tokens and $30 per million output tokens, and the Batch API applies a 50% discount for asynchronous jobs. Third-party providers resell access at their own rates, some starting near $0.025 per image.

The biggest difference is the reasoning step GPT Image 2 performs before generation, which improves prompt adherence and how sensibly objects are arranged in a scene. The second major upgrade is text: GPT Image 2 renders typography inside images far more reliably than its predecessor, including CJK scripts. It also supports larger custom dimensions, with a maximum edge of 3840px, where earlier GPT Image output was limited to a small set of presets like 1024x1024, 1536x1024, and 1024x1536.

GPT Image 2 offers preset square, portrait, and landscape sizes along with fully custom dimensions. Custom sizes must be multiples of 16, the longest edge can reach 3840px, aspect ratios go up to 3:1, and total output is capped around 8.3 million pixels. Supported output formats are PNG, JPEG, and WEBP. That range covers 4K hero images, ultra-wide banners, and vertical 9:16 frames intended for short-form video without a separate upscaling pass.

Yes. GPT Image 2 supports image editing with mask support, which covers both inpainting and outpainting. You can replace a single element, change a background, remove an object, or extend a frame into a wider or taller aspect ratio while leaving the rest of the composition untouched. This is generally cheaper and more predictable than regenerating the full image when only one region is wrong.

Yes, and it is the natural next step. A GPT Image 2 render makes an excellent opening frame for image-to-video generation because the composition and any on-image text are already correct. On VO3 you upload the still, add a short motion prompt describing how the scene should move, and the model animates it into a clip. Keeping the motion simple preserves the text fidelity and fine detail that make GPT Image 2 images worth animating in the first place.

It is one of the stronger options available, mainly because of the text rendering. Packaging mockups, ad creative with headlines, menu boards, and marketplace listing images all depend on legible type, and that was the failure point of previous models. Combined with 4K output and mask-based editing for revisions, GPT Image 2 fits real production workflows. Note that usage rights and brand safety still depend on OpenAI's terms and your own review process, so treat generated assets the way you would any other licensed creative.

OpenAI followed with GPT Image 2.5 on September 8, 2026, which introduced a Sketch feature and split API access into two variants, Flare and Sunburst, trading off speed against quality. GPT Image 2 itself remains widely available and well supported, and the image-to-video workflow is identical either way: generate the still with whichever tier suits your budget, then animate it on VO3.

The closest competitors are Google's Nano Banana 2 family, which is cheaper and faster but weaker on dense text, Seedream 5 for stylized and photographic work, and FLUX 3 for open-weight flexibility. GPT Image 2 wins when typography, layout reasoning, or 4K output matter most; the alternatives win on price per image and raw speed. If your end goal is video, the choice matters less than you would think, since VO3 accepts a starting frame from any of them.