Media Generation
Image Generation
Generate images using gemini-3.1-flash-image-preview.
from google import genai
from google.genai import types
client = genai.Client()
response = client.models.generate_content(
model="gemini-3.1-flash-image-preview",
contents="A dog reading a newspaper",
)
for part in response.parts:
if part.text is not None:
print(part.text)
elif part.inline_data is not None:
image = part.as_image()
image.save("generated_image.png")For high-resolution images or using the Search tool, use gemini-3-pro-image-preview.
from google import genai
from google.genai import types
client = genai.Client()
response = client.models.generate_content(
model="gemini-3-pro-image-preview",
contents="A dog reading a newspaper",
config=types.GenerateContentConfig(
image_config=types.ImageConfig(
aspect_ratio="16:9",
image_size="2K"
)
)
)
for part in response.parts:
if part.text is not None:
print(part.text)
elif part.inline_data is not None:
image = part.as_image()
image.save("generated_image.png")Image Editing
It is recommended to use chat mode for editing images.
from google import genai
from PIL import Image
client = genai.Client()
prompt = "A small white ceramic bowl with lemons and limes"
image = Image.open('fruit.png')
# Create the chat
chat = client.chats.create(model='gemini-3.1-flash-image-preview')
# Send the image and ask for it to be edited
response = chat.send_message([prompt, image])
# Get the text and the image generated
for i, part in enumerate(response.candidates[0].content.parts):
if part.text is not None:
print(part.text)
elif part.inline_data is not None:
image = part.as_image()
image.save(f'generated_image_{i}.png')
# Continue iterating
chat.send_message('Make the bowl blue')Video Generation
Generate video using the Veo model. Usage of Veo can be costly, so check pricing for Veo. Start with the fast model (veo-3.1-fast-generate-001) since the result quality is usually sufficient, and swap to the larger model if needed.
import time
from google import genai
from google.genai import types
from PIL import Image
client = genai.Client()
image = Image.open('image.png') # Optional initial image
# Video generation is an async operation
operation = client.models.generate_videos(
model="veo-3.1-fast-generate-001",
prompt="a cat reading a book",
image=image,
config=types.GenerateVideosConfig(
person_generation="dont_allow",
aspect_ratio="16:9",
number_of_videos=1,
duration_seconds=5,
output_gcs_uri="gs://your-bucket/your-prefix",
),
)
# Poll for completion
while not operation.done:
time.sleep(20)
operation = client.operations.get(operation)
if operation.response:
print(operation.result.generated_videos[0].video.uri)