GPT Image 2

GPT Image 2 transforms natural language descriptions into high-quality images with remarkable precision. Simply describe what you want — a product shot, a landscape, a character design — and the model interprets your prompt with exceptional fidelity. It understands complex compositional instructions, allowing you to specify layout, style, color palette, and text placement all within a single prompt. The deep language understanding ensures that even nuanced or creative prompts are accurately translated into visual output.

Text rendering has long been the Achilles' heel of AI image generators. GPT Image 2 changes that completely. It can accurately render multi-word phrases, brand names, street signs, book covers, product packaging, and user interface labels directly within generated images. The text produced maintains correct perspective, follows surface curvature, and interacts naturally with scene lighting. This makes it uniquely valuable for marketing materials, app mockups, and any project requiring readable text.

GPT Image 2 is not just a generation tool — it's a powerful editor. With GPT Image 2 inpainting capabilities, you can modify specific regions of an existing image while preserving the rest. Need to change a product's color, add an object, or remove an unwanted element? GPT Image 2 handles these edits with contextual awareness, ensuring changes blend seamlessly with the original image. The edit API supports both mask-based and prompt-driven modifications.

GPT Image 2 supports image-to-image workflows, allowing you to transform existing visuals into new styles or variations. Upload a reference image and let GPT Image 2 reimagine it in a different artistic style, adjust the lighting, or change the season. GPT Image 2 maintains structural coherence while applying creative transformations, making it ideal for iterative design processes and style exploration.

GPT Image 2 can accept multiple reference images simultaneously, enabling complex creative workflows. Provide a style reference, a composition guide, and a subject image, and it will synthesize all inputs into a cohesive output. This multi-reference capability gives creators fine-grained control over the final result without requiring extensive prompt engineering.

GPT Image 2 draws on a vast understanding of real-world concepts, objects, and contexts. When you ask it to generate a kitchen scene, the model knows what appliances look like, how countertops reflect light, and where utensils belong. It applies this knowledge to create images that feel authentic and grounded, reducing the need for multiple regeneration attempts. This world knowledge also helps render culturally accurate scenes and objects.