Are nano-banana-2-lite and the original nano-banana the same model?
No. Lite corresponds to Gemini 3.1 Flash Lite Image, while the original Nano Banana corresponds to Gemini 2.5 Flash Image. When making calls, you should explicitly specify nano-banana-2-lite; do not omit the model name simply because both belong to the Nano Banana service, or assume the two versions have exactly the same capabilities.
Can Lite generate 2K or 4K images?
2K and 4K cannot be regarded as Lite's native output capabilities; its only resolution tier is 1K. If a project requires higher resolution, consider Nano Banana 2 or Pro. Changing the aspect ratio and selecting a higher resolution are different operations; portrait or widescreen compositions do not mean more detail.
How do I submit an image editing task?
When using /nano-banana/images, select action=edit, provide images through image_urls, and enter editing instructions; when using /openai/images/edits, provide image and prompt, and explicitly specify the model. It is recommended to complete focused edits on a clear original image first, then assess whether to continue editing.
Is it suitable for repeatedly modifying the same person or product?
You can try simple edits, but Lite is not optimized for multi-turn continuous editing, so you should not expect identity and details to be strictly preserved in every round. When you need to continuously maintain a person's appearance, product structure, or relationships among multiple reference assets, the standard Nano Banana 2 is better suited to such tasks, and each round should still be reviewed.
How can generated results be integrated into an application?
Images from the dedicated endpoint are located in data[].image_url; the OpenAI image endpoint result structure includes URL or Base64 data and also defines a task ID return format. Applications should distinguish between image results and task identifiers and save necessary records; all generated images contain a SynthID watermark.