Gemini Image Generation (Nano Banana Pro)

Generate and edit images using Google's Gemini API. The environment variable GEMINI_API_KEY must be set.

Default Model

Model Resolution Best For

gemini-3-pro-image-preview

1K-4K All image generation (default)

Note: Always use this Pro model. Only use a different model if explicitly requested.

Quick Reference

Default Settings

• Model: gemini-3-pro-image-preview

• Resolution: 1K (default, options: 1K, 2K, 4K)

• Aspect Ratio: 1:1 (default)

Available Aspect Ratios

1:1 , 2:3 , 3:2 , 3:4 , 4:3 , 4:5 , 5:4 , 9:16 , 16:9 , 21:9

Available Resolutions

1K (default), 2K , 4K

Core API Pattern

import os from google import genai from google.genai import types

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

Basic generation (1K, 1:1 - defaults)

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=["Your prompt here"], config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'], ), )

for part in response.parts: if part.text: print(part.text) elif part.inline_data: image = part.as_image() image.save("output.png")

Custom Resolution & Aspect Ratio

from google.genai import types

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=[prompt], config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'], image_config=types.ImageConfig( aspect_ratio="16:9", # Wide format image_size="2K" # Higher resolution ), ) )

Resolution Examples

1K (default) - Fast, good for previews

image_config=types.ImageConfig(image_size="1K")

2K - Balanced quality/speed

image_config=types.ImageConfig(image_size="2K")

4K - Maximum quality, slower

image_config=types.ImageConfig(image_size="4K")

Aspect Ratio Examples

Square (default)

image_config=types.ImageConfig(aspect_ratio="1:1")

Landscape wide

image_config=types.ImageConfig(aspect_ratio="16:9")

Ultra-wide panoramic

image_config=types.ImageConfig(aspect_ratio="21:9")

Portrait

image_config=types.ImageConfig(aspect_ratio="9:16")

Photo standard

image_config=types.ImageConfig(aspect_ratio="4:3")

Editing Images

Pass existing images with text prompts:

from PIL import Image

img = Image.open("input.png") response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=["Add a sunset to this scene", img], config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'], ), )

Multi-Turn Refinement

Use chat for iterative editing:

from google.genai import types

chat = client.chats.create( model="gemini-3-pro-image-preview", config=types.GenerateContentConfig(response_modalities=['TEXT', 'IMAGE']) )

response = chat.send_message("Create a logo for 'Acme Corp'")

Save first image...

response = chat.send_message("Make the text bolder and add a blue gradient")

Save refined image...

Prompting Best Practices

Photorealistic Scenes

Include camera details: lens type, lighting, angle, mood.

"A photorealistic close-up portrait, 85mm lens, soft golden hour light, shallow depth of field"

Stylized Art

Specify style explicitly:

"A kawaii-style sticker of a happy red panda, bold outlines, cel-shading, white background"

Text in Images

Be explicit about font style and placement:

"Create a logo with text 'Daily Grind' in clean sans-serif, black and white, coffee bean motif"

Product Mockups

Describe lighting setup and surface:

"Studio-lit product photo on polished concrete, three-point softbox setup, 45-degree angle"

Advanced Features

Google Search Grounding

Generate images based on real-time data:

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=["Visualize today's weather in Tokyo as an infographic"], config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'], tools=[{"google_search": {}}] ) )

Multiple Reference Images (Up to 14)

Combine elements from multiple sources:

response = client.models.generate_content( model="gemini-3-pro-image-preview", contents=[ "Create a group photo of these people in an office", Image.open("person1.png"), Image.open("person2.png"), Image.open("person3.png"), ], config=types.GenerateContentConfig( response_modalities=['TEXT', 'IMAGE'], ), )

Important: File Format & Media Type

CRITICAL: The Gemini API returns images in JPEG format by default. When saving, always use .jpg extension to avoid media type mismatches.

CORRECT - Use .jpg extension (Gemini returns JPEG)

image.save("output.jpg")

WRONG - Will cause "Image does not match media type" errors

image.save("output.png") # Creates JPEG with PNG extension!

Converting to PNG (if needed)

If you specifically need PNG format:

from PIL import Image

Generate with Gemini

for part in response.parts: if part.inline_data: img = part.as_image() # Convert to PNG by saving with explicit format img.save("output.png", format="PNG")

Verifying Image Format

Check actual format vs extension with the file command:

file image.png

If output shows "JPEG image data" - rename to .jpg!

Notes

• All generated images include SynthID watermarks

• Gemini returns JPEG format by default - always use .jpg extension

• Image-only mode (responseModalities: ["IMAGE"] ) won't work with Google Search grounding

• For editing, describe changes conversationally—the model understands semantic masking

• Default to 1K resolution for speed; use 2K/4K when quality is critical