NanoBanana Image Generation

Generate and edit AI images through AceDataCloud's NanoBanana (Gemini-based) API.

Setup: See [authentication](../_shared/authentication.md) for token setup.

Quick Start

curl -X POST https://api.acedata.cloud/nano-banana/images \
  -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"action": "generate", "prompt": "a watercolor painting of a French countryside village", "model": "nano-banana"}'

Async: See [async task polling](../_shared/async-tasks.md). Poll via POST /nano-banana/tasks with {"id": "..."}.

Models

Workflows

1. Text-to-Image

POST /nano-banana/images
{
  "action": "generate",
  "prompt": "a photorealistic macro shot of morning dew on a spider web",
  "model": "nano-banana-pro",
  "aspect_ratio": "16:9",
  "resolution": "2K"
}

2. Image Editing

Edit existing images using natural language instructions — no mask needed. Pass source images via image_urls.

POST /nano-banana/images
{
  "action": "edit",
  "prompt": "change the background to a starry night sky",
  "image_urls": ["https://example.com/photo.jpg"],
  "model": "nano-banana"
}

Parameters

Gotchas

• Editing does NOT require a mask — just describe the change in natural language
• Editing uses the same /nano-banana/images endpoint with action: "edit" and image_urls array (not a separate /edit path)
• nano-banana-2 is the second-generation model; nano-banana-pro offers the highest quality
• :official variants (e.g., nano-banana:official) route through the official channel
• Task polling uses id (not task_id) in the /nano-banana/tasks request body
• Aspect ratio uses colon notation (e.g., "16:9") not pixel dimensions
• The Gemini-based model excels at understanding complex, conversational editing instructions

MCP: pip install mcp-nano-banana | Hosted: https://nanobanana.mcp.acedata.cloud/mcp | See [all MCP servers](../_shared/mcp-servers.md)