nano-banana-pro

Nano Banana Pro is the marketing name for Gemini 3 Pro Image (gemini-3-pro-image-preview), Google's state-of-the-art image generation and editing model built on Gemini 3 Pro.

Get API Key

1. Go to [Google AI Studio](https://aistudio.google.com)
2. Click "Get API Key"
3. Store securely as environment variable

Basic Image Generation (Python)

```python

from google import genai

from google.genai import types

client = genai.Client(api_key="YOUR_GEMINI_API_KEY")

response = client.models.generate_content(

model="gemini-3-pro-image-preview",

contents="A serene Japanese garden with cherry blossoms and a koi pond",

config=types.GenerateContentConfig(

response_modalities=['TEXT', 'IMAGE']

)

)

# Process response

for part in response.candidates[0].content.parts:

if hasattr(part, 'text'):

print(f"Description: {part.text}")

elif hasattr(part, 'inline_data'):

# Save image

image_data = part.inline_data.data # Base64 encoded

mime_type = part.inline_data.mime_type # image/png

import base64

with open("output.png", "wb") as f:

f.write(base64.b64decode(image_data))

```

REST API (cURL)

```bash

curl -s -X POST \

"https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \

-H "x-goog-api-key: $GEMINI_API_KEY" \

-H "Content-Type: application/json" \

-d '{

"contents": [{

"role": "user",

"parts": [{"text": "Create a vibrant infographic about photosynthesis"}]

}],

"generationConfig": {

"responseModalities": ["TEXT", "IMAGE"]

}

}'

```

TypeScript/JavaScript

```typescript

const GEMINI_API_KEY = process.env.GEMINI_API_KEY;

async function generateImage(prompt: string) {

const response = await fetch(

'https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent',

{

method: 'POST',

headers: {

'x-goog-api-key': GEMINI_API_KEY!,

'Content-Type': 'application/json',

},

body: JSON.stringify({

contents: [{

role: 'user',

parts: [{ text: prompt }]

}],

generationConfig: {

responseModalities: ['TEXT', 'IMAGE'],

},

}),

}

);

const data = await response.json();

return data;

}

```

Image Configuration

```python

response = client.models.generate_content(

model="gemini-3-pro-image-preview",

contents="Professional product photo of a coffee mug",

config=types.GenerateContentConfig(

response_modalities=['TEXT', 'IMAGE'],

image_config=types.ImageConfig(

aspect_ratio="16:9", # Options: 1:1, 3:2, 16:9, 9:16, 21:9

image_size="2K" # Options: 1K, 2K, 4K

)

)

)

```

With Google Search Grounding

```python

response = client.models.generate_content(

model="gemini-3-pro-image-preview",

contents="Create an infographic showing today's stock market trends",

config=types.GenerateContentConfig(

response_modalities=['TEXT', 'IMAGE'],

tools=[{"google_search": {}}] # Enable search grounding

)

)

```

```python

# Create a chat session

chat = client.chats.create(

model="gemini-3-pro-image-preview",

config=types.GenerateContentConfig(

response_modalities=['TEXT', 'IMAGE'],

tools=[{"google_search": {}}]

)

)

# Initial generation

response1 = chat.send_message(

"Create a vibrant infographic explaining photosynthesis"

)

# Edit the image

response2 = chat.send_message(

"Update this infographic to be in Spanish. Keep all other elements the same."

)

```

1. Superior Text Rendering

```python

response = client.models.generate_content(

model="gemini-3-pro-image-preview",

contents="""Create a professional poster with:

- Title: "Annual Tech Summit 2025"

- Date: March 15-17, 2025

- Location: San Francisco Convention Center

""",

config=types.GenerateContentConfig(

response_modalities=['TEXT', 'IMAGE']

)

)

```

2. Character Consistency (Up to 5 Subjects)

```python

import base64

def load_image(path: str) -> str:

with open(path, "rb") as f:

return base64.b64encode(f.read()).decode()

character_ref = load_image("character.png")

response = client.models.generate_content(

model="gemini-3-pro-image-preview",

contents=[

{"text": "Generate an image of this person at a tech conference"},

{"inline_data": {"mime_type": "image/png", "data": character_ref}}

],

config=types.GenerateContentConfig(

response_modalities=['TEXT', 'IMAGE']

)

)

```

```typescript

// app/api/generate-image/route.ts

import { NextRequest, NextResponse } from 'next/server';

export async function POST(request: NextRequest) {

const { prompt, aspectRatio = '1:1', imageSize = '2K' } = await request.json();

try {

const response = await fetch(

'https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent',

{

method: 'POST',

headers: {

'x-goog-api-key': process.env.GEMINI_API_KEY!,

'Content-Type': 'application/json',

},

body: JSON.stringify({

contents: [{ role: 'user', parts: [{ text: prompt }] }],

generationConfig: {

responseModalities: ['TEXT', 'IMAGE'],

imageConfig: { aspectRatio, imageSize },

},

}),

}

);

const data = await response.json();

const parts = data.candidates?.[0]?.content?.parts || [];

const imagePart = parts.find((p: any) => p.inline_data);

return NextResponse.json({

image: imagePart ? {

data: imagePart.inline_data.data,

mimeType: imagePart.inline_data.mime_type,

url: data:${imagePart.inline_data.mime_type};base64,${imagePart.inline_data.data},

} : null,

});

} catch (error) {

return NextResponse.json({ error: 'Generation failed' }, { status: 500 });

}

}

```

| Feature | Nano Banana (2.5 Flash) | Nano Banana Pro (3 Pro Image) |

|---------|-------------------------|-------------------------------|

| Model ID | gemini-2.5-flash-image | gemini-3-pro-image-preview |

| Quality | Good | Best |

| Speed | Faster | Slower |

| Cost | Lower | Higher |

| Best For | Previews, high-volume | Production, professional |

• Documentation: https://ai.google.dev/gemini-api/docs/image-generation
• Google AI Studio: https://aistudio.google.com
• Prompt Guide: https://ai.google.dev/gemini-api/docs/prompting-intro