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