Nano Banana 2 does not natively generate images at 4K resolution in a single inference pass. The model's native output resolution tops out at 1024×1024 pixels for square outputs, with proportionally adjusted dimensions for other aspect ratios. Generating at resolutions above this threshold requires a post-processing upscaling step, either using a dedicated upscaling model or a third-party upscaling service, applied after the base image is returned by the API. The API documentation specifies the exact maximum pixel dimensions for each supported aspect ratio, and requests that exceed those dimensions will return a validation error rather than silently downscaling your request.
For production workflows that genuinely need 4K output—such as print-ready assets, large-format display graphics, or high-resolution textures for 3D applications—the standard approach is to generate at the highest native resolution and then apply a 2x or 4x AI upscaler. Models specifically trained for upscaling tend to preserve edge detail and texture better than interpolation-based methods. Some teams also tile the generation by prompting for different sections of a large image independently and compositing the results, though this requires careful attention to seams and stylistic consistency across tiles.
The Pro tier of the model family supports higher native output resolutions than Nano Banana 2, so if 4K or near-4K native output is a firm requirement for your application, evaluating the Pro tier is worth the additional cost. For most web applications, social media assets, and UI mockups, however, the 1024×1024 native ceiling of Nano Banana 2 combined with a software upscaling pass produces results that are indistinguishable from native high-resolution output at typical viewing sizes.