Nano Banana Images API Integration Guide
This document introduces the integration and use of the Nano Banana Images API. This API supports two capabilities: image generation (generate) and image editing (edit).
¶ Application Process
To use the Nano Banana Images API, first go to the qiyaov Console to obtain your API Token and keep it for later use.

If you have not yet logged in or registered, you will be automatically redirected to the login page and invited to register and log in. After completion, you will automatically return to the current page.
One API Token can call all platform services; there is no need to apply separately for each service. Your first application includes free credits for a free trial; when credits are insufficient, you can recharge your general balance in the Console.
📘 Full documentation: Nano Banana Images API →
¶ API Overview
- Base URL:
https://api.qiyaov.com - Endpoint:
POST /nano-banana/images - Authentication method: Include
authorization: Bearer {token}in the HTTP Header - Request headers:
accept: application/jsoncontent-type: application/json
- Action (
action):generate: Generate an image based on a text promptedit: Edit based on the given image
- Model (
model) (optional):nano-banana(default): Based on Gemini 2.5 Flash Image, fast and low costnano-banana-2-lite: Based on Gemini 3.1 Flash Lite Image, supports 1K only, fast generation speednano-banana-2: Based on Gemini 3.1 Flash Image Preview, Pro-level quality + Flash speednano-banana-pro: Based on Gemini 3 Pro Image Preview, highest qualitynano-banana:official,nano-banana-2-lite:official,nano-banana-2:official,nano-banana-pro:official: Official channel versions of the corresponding models, with better image quality and stability, billed differently
- Asynchronous callback: Optional; receive task completion notifications and results through
callback_url - Image quantity: Optional; specify 1–4 images through
count, with a default of 1; each image is completed by an independent generation call; ordinary technical failures or provider safety rejections only affect the corresponding call, while other successful images are returned as usual and billed according to the actual number of successful images
¶ Quick Start: Generate Images (action=generate)
Minimum required parameters: action, prompt
When you only want to directly generate an image based on a prompt, set action to generate and provide a clear prompt.
¶ Request Example (cURL)
curl -X POST 'https://api.qiyaov.com/nano-banana/images' \
-H 'authorization: Bearer {token}' \
-H 'accept: application/json' \
-H 'content-type: application/json' \
-d '{
"action": "generate",
"model": "nano-banana-pro",
"prompt": "A photorealistic close-up portrait of an elderly Japanese ceramicist with deep, sun-etched wrinkles and a warm, knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic, sun-drenched workshop. The scene is illuminated by soft, golden hour light streaming through a window, highlighting the fine texture of the clay. Captured with an 85mm portrait lens, resulting in a soft, blurred background (bokeh). The overall mood is serene and masterful. Vertical portrait orientation.",
"count": 1
}'
¶ Request Example (Python)
import requests
url = "https://api.qiyaov.com/nano-banana/images"
headers = {
"authorization": "Bearer {token}",
"accept": "application/json",
"content-type": "application/json",
}
payload = {
"action": "generate",
"model": "nano-banana-pro",
"prompt": (
"A photorealistic close-up portrait of an elderly Japanese ceramicist "
"with deep, sun-etched wrinkles and a warm, knowing smile. He is carefully "
"inspecting a freshly glazed tea bowl. The setting is his rustic, sun-drenched "
"workshop. The scene is illuminated by soft, golden hour light streaming through "
"a window, highlighting the fine texture of the clay. Captured with an 85mm "
"portrait lens, resulting in a soft, blurred background (bokeh). The overall mood "
"is serene and masterful. Vertical portrait orientation."
),
"count": 1
}
resp = requests.post(url, json=payload, headers=headers)
print(resp.json())
¶ Successful Response Example
{
"success": true,
"task_id": "70e6931b-6e34-43db-9e36-8765e2809d04",
"trace_id": "60df8d38-f265-4986-aec7-75c9220bced2",
"data": [
{
"prompt": "A photorealistic close-up portrait of an elderly Japanese ceramicist with deep, sun-etched wrinkles and a warm, knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic, sun-drenched workshop. The scene is illuminated by soft, golden hour light streaming through a window, highlighting the fine texture of the clay. Captured with an 85mm portrait lens, resulting in a soft, blurred background (bokeh). The overall mood is serene and masterful. Vertical portrait orientation.",
"image_url": "https://cdn.acedata.cloud/assets/examples/nanobanana/1d0160b4-93f9-4229-8926-ea9ef0bed336-34b3dc2195e8.png"
}
]
}
¶ Field Descriptions
success: Whether this request was successful.task_id: Task ID.trace_id: Trace ID for troubleshooting.count: The number of images requested for generation or editing, supporting 1–4, with a default of 1.datacontains only successfully generated images and is billed according to the actual number returned. Each generation call is required to use the provider's native safety policy; rejection of one call does not affect other successful calls, and 403 is returned when all calls are rejected.data[]: Result list.prompt: Prompt used for generation (echoed back).image_url: Direct URL of the generated image.
Note:
/nano-banana/imagesonly requiresactionandpromptto generate images
¶ Edit Images (action=edit)
When you want to edit based on an existing image, set action to edit, pass in the list of image links to be edited (one or more images) through image_urls, and provide a prompt describing the editing target.
For example, here we provide a portrait photo and a clothing photo, and have the person wear the clothing. You can pass in both image links at the same time and specify action as edit. The URL can be an HTTP URL, a publicly accessible link using the https or http protocol, or a Base64-encoded image, such as data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA+gAAAVGCAMAAAA6u2FyAAADAFBMVEXq6uwdHCEeHyMdHS....
¶ Request Example (cURL)
curl -X POST 'https://api.qiyaov.com/nano-banana/images' \
-H 'authorization: Bearer {token}' \
-H 'accept: application/json' \
-H 'content-type: application/json' \
-d '{
"action": "edit",
"prompt": "let this man wear on this T-shirt",
"image_urls": [
"https://cdn.acedata.cloud/v8073y.png",
"https://cdn.acedata.cloud/44xlah.png"
],
"count": 1
}'
¶ Request Example (Python)
import requests
url = "https://api.qiyaov.com/nano-banana/images"
headers = {
"authorization": "Bearer {token}",
"accept": "application/json",
"content-type": "application/json",
}
payload = {
"action": "edit",
"prompt": "let this man wear on this T-shirt",
"image_urls": [
"https://cdn.acedata.cloud/v8073y.png",
"https://cdn.acedata.cloud/44xlah.png"
],
"count": 1
}
resp = requests.post(url, json=payload, headers=headers)
print(resp.json())
¶ Successful Response Example
{
"success": true,
"task_id": "93f11baf-347b-4bb4-9520-8653cb46d6a3",
"trace_id": "a9063166-26ed-4451-85b5-54e896817c69",
"data": [
{
"prompt": "let this man wear on this T-shirt",
"image_url": "https://platform.cdn.acedata.cloud/nanobanana/8e9e0253-26f4-45b9-b3f8-ac1aed1c284b.png"
}
]
}
¶ Field Description
image_urls[]: List of image URLs to be edited (must be publicly accessible). Multiple images can be provided, and the service will combine these materials with thepromptto complete the editing.- Other fields are the same as those returned by "Generate Image".
¶ Asynchronous Callback (Optional, Recommended)
Generation or editing may take some time. To avoid long connections consuming resources, it is recommended to use a Webhook callback through callback_url:
- Add
callback_urlto the request body, for example, your server-side Webhook address (must be publicly accessible and support POST JSON). - The API will immediately return a response containing
task_id(or basic results). - When the task is completed, the platform will send the complete JSON to
callback_urlviaPOST. You can associate the request with the result throughtask_id.
Callback Payload Example (the field structure is consistent with the synchronous successful response):
{
"success": true,
"task_id": "6a97bf49-df50-4129-9e46-119aa9fca73c",
"trace_id": "9b4b1ff3-90f2-470f-b082-1061ec2948cc",
"data": [
{
"prompt": "a white siamese cat",
"image_url": "https://platform.cdn.acedata.cloud/nanobanana/xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx.png"
}
]
}
¶ Error Handling
When a call fails, a standard error format and trace ID will be returned. Common errors are as follows:
- 400
token_mismatched: The request is invalid or there is a parameter error. - 400
api_not_implemented: The API is not implemented (please contact support). - 401
invalid_token: Authentication failed or the Token is missing. - 403
forbidden: The provider's native security policy rejected the request or generated result. This call will not return an image and will not be billed; multi-image requests may still return and bill for other successful calls. - 429
too_many_requests: Request rate limit exceeded. - 500
api_error: Server-side exception.
¶ Error Response Example
{
"success": false,
"error": {
"code": "api_error",
"message": "Internal server error."
},
"trace_id": "2cf86e86-22a4-46e1-ac2f-032c0f2a4e89"
}
¶ Parameter Reference and Notes
- Required:
action,prompt - Editing Only:
image_urls(array, at least 1 item) - Optional:
model(default:nano-banana; optional values:nano-banana-2-lite,nano-banana-2,nano-banana-pro, or the corresponding:officialofficial channel versions),aspect_ratio(aspect ratio, such as1:1,16:9),resolution(resolution, such as1K,2K,4K;nano-banana-2-litesupports only1K),callback_url(used for asynchronous callbacks) - Headers: You must provide
authorization: Bearer {token}; settingaccepttoapplication/jsonis recommended - Image Accessibility:
image_urlsmust be publicly accessible direct links (HTTP/HTTPS); HTTPS is recommended - Idempotency and Tracking: Retain
task_idandtrace_idfor troubleshooting and result association