GPT Image 2 runs a native reasoning pass that plans the composition, counts the objects a prompt asks for, and verifies spatial and compositional constraints before rendering. The result is dramatically fewer miscounts, fewer mislabeled diagrams, and far fewer wasted credits chasing a reroll a diffusion model would miss.

Output images at 2K by default — no upscaling pass, no post-processing to reach print-ready fidelity. Detail, typography, skin texture, and material reflections all hold up under scrutiny, so creatives ship directly from prompt to poster, ad, or hero banner.

Small UI labels, logos, captions, and non-Latin scripts — including Japanese, Korean, Chinese, Hindi, and Bengali — render cleanly enough to ship without a manual redraw. Finally: legible, typographically coherent text on the first generation.

Generate up to eight coherent images from a single prompt — character turnarounds, storyboards, product lineups, and campaign variants that share a unified visual identity, pose library, and lighting across every frame.

Upload a reference image (up to 16 in image-to-image mode) and describe a change. GPT Image 2 preserves the rest of the image at pixel-level fidelity while applying surgical edits — remove an object, swap wardrobe, change lighting, or add a subject — without Photoshop in the loop.

In reasoning mode the model draws on stronger world knowledge to ground diagrams, charts, and maps — correct labels, plausible proportions, plausible numerics — making technical and educational visuals shippable rather than decorative.