GPT Image Models

What separates GPT Image from diffusion-first rivals is instruction following. Ask for "a kitchen scene with exactly three copper pots hanging to the left of the window, morning light, a cat asleep on the counter" and GPT Image 2 will count the pots, place them on the correct side, and remember the cat. That spatial and numerical reliability makes it the model marketers reach for when a brief has non-negotiable details: a storefront mockup with the shop name on the awning, an editorial illustration where the subject must face a specific direction, or a recipe header where every listed ingredient actually appears.

The second pillar is the editing pipeline. GPT Image-1.5 performs targeted inpainting that most generators fumble: swap a model's outfit, recolour a car, or clear clutter off a desk while the rest of the frame stays untouched. Paired with GPT Image 2 for the initial render, the two versions cover a full create-then-refine loop without leaving OpenAI's stack.

Know the limits before committing. Output resolution caps near 1120x1120 px, so print work needs an upscaling pass. Per-image cost sits above draft-tier models, which makes GPT Image a poor fit for spraying fifty variations at a vague idea - the FLUX lineup handles that volume game far more economically. And while its photorealism is excellent, it tends toward a polished, evenly lit look; if you want output that reads like a specific camera and lens captured it, Lucid Realism chases that aesthetic more single-mindedly.

Pick GPT Image when the brief is precise, the deliverable is singular, and you would rather describe than engineer. It is the closest thing on the platform to handing your idea to a professional and getting back exactly what you asked for.