Model:
Price: from 60 credits per request · ≈ $0.03High stability with detailed usage records on the APIAny platform.
Use reference images
Leave off for text-to-image. Turn on to upload or paste up to 14 reference images.
Output aspect ratio. Custom WxH pixel sizes remain accepted in JSON mode when supported upstream.
Output quality tier.
USD estimate ≈ $0.05: $999 tier: $1 = 2,000 credits.
Real image and video examples made through our models. Preview freely; using a preset never starts generation.
Actual generation model: nano-banana-pro
{
"model": "nano-banana-pro",
"prompt": "Edit the supplied interior photograph. Preserve the room geometry, windows and camera position. Restyle only the furniture with restrained mid-century oak pieces and warm woven upholstery, retaining realistic scale and natural light. No text, letters, numbers, labels, branding, logos, watermark, interface, captions or graphic overlays anywhere in the image. One coherent scene, no collage.",
"size": "16:9",
"quality": "2K",
"image_urls": [
"https://s.apiany.ai/web-static/mode-infos/v2/2026-09-20/d12-natural-interior/image.webp"
]
}History
Saved locally in this browser
0 running · 0 completed
Billing Rules
Authentication
Every request needs a Bearer token in the Authorization header. Create an API key in the console.
Authorization: Bearer YOUR_API_KEYhttps://apiany.ai/v1/images/generationsRequest parameters
| Parameter | Type | Required | Notes |
|---|---|---|---|
model | string | Required | Model identifier to invoke. Use this model's ID. |
prompt | string | Required | Text prompt describing what you want to generate. |
size | string | Optional | Output aspect ratio. Custom WxH pixel sizes remain accepted in JSON mode when supported upstream. · Options: auto, 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9 · Default: auto |
quality | string | Optional | Output quality tier. · Options: 1K, 2K, 4K · Default: 2K |
callback_url | string | Optional | Optional webhook URL called when the async task finishes. |
Request example
curl "https://apiany.ai/v1/images/generations" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "nano-banana-pro",
"prompt": "Edit the supplied interior photograph. Preserve the room geometry, windows and camera position. Restyle only the furniture with restrained mid-century oak pieces and warm woven upholstery, retaining realistic scale and natural light. No text, letters, numbers, labels, branding, logos, watermark, interface, captions or graphic overlays anywhere in the image. One coherent scene, no collage.",
"size": "auto",
"quality": "2K"
}'Response example
{
"task_id": "task_abc123",
"status": "pending",
"poll_url": "/v1/tasks/task_abc123",
"request_id": "req_abc123",
"credits": {
"reserved": 1000
}
}This endpoint is asynchronous: it returns a task_id immediately. Poll the task-status endpoint until status becomes succeeded, then read the result. Generated media links stay valid for 24 hours.
Model overview
Google Nano Banana Pro targets high-fidelity image generation and editing with stronger detail, composition control, and reference consistency for demanding production work.
Start with the desired visual outcome, references, and delivery format, then shape the generation workflow around them.
Nano Banana Pro is available on APIAny as one documented API surface with live pricing, model status, request examples, and an on-page playground. Teams can evaluate the model here, then keep authentication, usage records, and production routing in the same platform.
Try Nano Banana Pro in the playground
Sources
The quotations below are from official API documentation that APIAny implements against.
The Gemini API provides access to Google's most capable generative AI models.
The Images API provides several endpoints that let you generate images from text prompts or create edits of existing images.
Use cases
The Nano Banana Pro API is used for product workflows that need this model's output. Test the same inputs in the playground, compare related models, and choose the route that meets your quality, latency, and budget requirements.
01
Use Nano Banana Pro to create visual directions for launches, ads, landing pages, and social campaigns. Standardize prompts and reference assets so a team can compare variants without rebuilding the generation workflow.
Try Nano Banana Pro in the playground
02
Generate product scenes, catalog assets, presentation imagery, or review-ready content with Nano Banana Pro. Batch requests through the API when a catalog needs consistent formats and repeatable output.
Try Nano Banana Pro in the playgroundCore capabilities
Nano Banana Pro API features are the input, output, and workflow traits that matter when you evaluate this model. Available request parameters remain visible in the live API reference on this page.
/01
Describe the requested output or task in text and send it through the documented Nano Banana Pro API request.
/02
Provide supported image inputs to guide editing, visual identity, composition, or motion in Nano Banana Pro workflows.
/03
Use Nano Banana Pro when detail, consistency, visual coherence, or polished production quality matters more than minimum latency.
/04
Select supported quality or resolution tiers when the final Nano Banana Pro asset needs more detail for review or delivery.
/05
APIAny advantages
Nano Banana Pro on APIAny is a production route with one key, live prices, status, and usage records, so you do not maintain a separate provider integration.
Call Nano Banana Pro with an APIAny key and a documented request format. Keep your application integration stable while model versions and upstream routes evolve behind the gateway.
Review the live Nano Banana Pro pricing rules before a request, estimate credits in the playground, and inspect request-level usage records after the call completes.
Integration
Integrating the Nano Banana Pro API is a three-step path from playground test to authenticated production request. The page keeps the model identifier, request schema, pricing, and response examples together. Treat generation as an asynchronous media pipeline with durable task tracking, validation, and asset delivery.
Sign in to APIAny, create a project API key, and assign only the model scope and budget controls your application needs.
Copy the request example from this page, set the model field to the selected Nano Banana Pro version, and send it to the documented APIAny endpoint.
Track status, latency, credits, and returned usage. Compare versions or related models with the same workload before shifting production traffic.
FAQ
Direct answers about capabilities, use cases, integration, and choosing the right Nano Banana Pro route.
Google Nano Banana Pro targets high-fidelity image generation and editing with stronger detail, composition control, and reference consistency for demanding production work. APIAny makes this model callable through an authenticated API with live pricing, status information, request examples, and a browser playground on the same page.
Common Nano Banana Pro workflows include Campaign and marketing visuals, Product and catalog content, Image editing and controlled revisions. The best fit depends on the input format, output quality, latency, and cost your product requires.
03
Use natural-language instructions and reference images to revise composition, style, objects, or local details with Nano Banana Pro. Keep the original brief and inputs in your workflow for repeatable review cycles.
Try Nano Banana Pro in the playground
Use supported reference assets to guide subject identity, style, composition, frames, or motion across generated results.
Use model status, channel health, retry policy, and usage logs to operate Nano Banana Pro as part of a production workflow instead of treating it as an isolated demo.
Create an APIAny key, use the endpoint documented on this page, and set the request model field to the selected Nano Banana Pro version. The playground can generate a working payload before you integrate it into application code.
Compare the versions shown on this page by price, supported parameters, and capabilities such as Text prompt input, Image and reference input, High-fidelity output. Test a representative production input before choosing the default route.
