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Video Generation Reference

Comprehensive guide for video creation using Veo models via Gemini API.

Core Capabilities

Text-to-Video: Generate 8-second videos from text prompts
Image-to-Video: Animate images with text direction
Video Extension: Continue previously generated videos
Frame Control: Precise camera movements and effects
Native Audio: Synchronized audio generation
Multiple Resolutions: 720p and 1080p output
Aspect Ratios: 16:9, 9:16, 1:1

Models

Veo 3.1 Preview (Latest)

veo-3.1-generate-preview - Latest with advanced controls

Frame-specific generation
Up to 3 reference images for image-to-video
Video extension capability
Native audio generation
Resolution: 720p, 1080p
Duration: 8 seconds at 24fps
Status: Preview (API may change)
Updated: September 2025

veo-3.1-fast-generate-preview - Speed-optimized

Optimized for business use cases
Programmatic ad creation
Social media content
Same features as standard but faster
Status: Preview
Updated: September 2025

Veo 3.0 Stable

veo-3.0-generate-001 - Production-ready

Native audio generation
Text-to-video and image-to-video
720p and 1080p (16:9 only)
8 seconds at 24fps
Status: Stable
Updated: July 2025

veo-3.0-fast-generate-001 - Stable fast variant

Speed-optimized stable version
Same reliability as 3.0
Status: Stable
Updated: July 2025

Model Comparison

Model	Speed	Features	Audio	Status	Best For
veo-3.1-preview	Medium	All	✓	Preview	Latest features
veo-3.1-fast	Fast	All	✓	Preview	Business/speed
veo-3.0-001	Medium	Standard	✓	Stable	Production
veo-3.0-fast	Fast	Standard	✓	Stable	Production/speed

Quick Start

Text-to-Video

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

client = genai.Client(api_key=os.getenv('GEMINI_API_KEY'))

# Basic generation
response = client.models.generate_video(
    model='veo-3.1-generate-preview',
    prompt='A serene beach at sunset with gentle waves rolling onto the shore',
    config=types.VideoGenerationConfig(
        resolution='1080p',
        aspect_ratio='16:9'
    )
)

# Save video
with open('output.mp4', 'wb') as f:
    f.write(response.video.data)

Image-to-Video

import PIL.Image

# Load reference image
ref_image = PIL.Image.open('beach.jpg')

# Animate the image
response = client.models.generate_video(
    model='veo-3.1-generate-preview',
    prompt='Camera slowly pans across the scene from left to right',
    reference_images=[ref_image],
    config=types.VideoGenerationConfig(
        resolution='1080p'
    )
)

Multiple Reference Images

# Use up to 3 reference images for complex scenes
img1 = PIL.Image.open('foreground.jpg')
img2 = PIL.Image.open('background.jpg')
img3 = PIL.Image.open('subject.jpg')

response = client.models.generate_video(
    model='veo-3.1-generate-preview',
    prompt='Combine these elements into a cohesive animated scene',
    reference_images=[img1, img2, img3],
    config=types.VideoGenerationConfig(
        resolution='1080p',
        aspect_ratio='16:9'
    )
)

Advanced Features

Video Extension

# Continue from previously generated video
previous_video = open('part1.mp4', 'rb').read()

response = client.models.extend_video(
    model='veo-3.1-generate-preview',
    video=previous_video,
    prompt='The scene transitions to nighttime with stars appearing'
)

Frame Control

# Precise camera movements
response = client.models.generate_video(
    model='veo-3.1-generate-preview',
    prompt='A mountain landscape',
    config=types.VideoGenerationConfig(
        resolution='1080p',
        camera_motion='zoom_in',  # Options: zoom_in, zoom_out, pan_left, pan_right, tilt_up, tilt_down, static
        motion_speed='slow'  # Options: slow, medium, fast
    )
)

Prompt Engineering

Effective Video Prompts

Structure:

Subject: What's in the scene
Action: What's happening
Camera: How it's filmed
Style: Visual treatment
Timing: Pacing details

Example:

"A hummingbird [subject] hovers near a red flower, then flies away [action].
Slow-motion close-up shot [camera] with vibrant colors and soft focus background [style].
Gentle, peaceful pacing [timing]."

Action Verbs

Movement:

"walks", "runs", "flies", "swims", "dances"
"rotates", "spins", "rolls", "bounces"
"emerges", "disappears", "transforms"

Camera:

"zoom in on", "pull back from", "follow"
"orbit around", "track alongside"
"tilt up to reveal", "pan across"

Transitions:

"gradually changes from... to..."
"morphs into", "dissolves into"
"cuts to", "fades to"

Timing Control

# Explicit timing in prompt
prompt = '''
0-2s: Close-up of a seed in soil
2-4s: Time-lapse of sprout emerging
4-6s: Growing into a small plant
6-8s: Zoom out to show garden context
'''

Configuration Options

Resolution

config = types.VideoGenerationConfig(
    resolution='1080p'  # Options: 720p, 1080p
)

Considerations:

1080p: Higher quality, longer generation time, larger file
720p: Faster generation, smaller file, good for drafts

Aspect Ratios

config = types.VideoGenerationConfig(
    aspect_ratio='16:9'  # Options: 16:9, 9:16, 1:1
)

Use Cases:

16:9: Landscape, YouTube, traditional video
9:16: Mobile, TikTok, Instagram Stories
1:1: Square, Instagram feed, versatile

Audio Control

config = types.VideoGenerationConfig(
    include_audio=True  # Default: True
)

Native audio is generated automatically and synchronized with video content.

Best Practices

1. Prompt Quality

Be specific:

❌ "A person walking"
✅ "A young woman in a red coat walking through a park in autumn"

Include motion:

❌ "A city street"
✅ "A busy city street with cars passing and people crossing"

Specify camera:

❌ "A mountain"
✅ "Aerial drone shot slowly ascending over a snow-capped mountain"

2. Reference Images

Quality:

Use high-resolution images (1080p+)
Clear, well-lit subjects
Minimal motion blur

Composition:

Match desired final aspect ratio
Leave room for motion/movement
Consider camera angle in prompt

3. Performance Optimization

Generation Time:

720p: ~30-60 seconds
1080p: ~60-120 seconds
Fast models: 30-50% faster

Strategies:

Use 720p for iteration/drafts
Use fast models for rapid feedback
Batch multiple requests
Use async processing for UI responsiveness

Common Use Cases

1. Product Demos

response = client.models.generate_video(
    model='veo-3.0-fast-generate-001',
    prompt='''
    Professional product video:
    - Sleek smartphone rotating on a pedestal
    - Clean white background with soft shadows
    - Slow 360-degree rotation
    - Spotlight highlighting premium design
    - Modern, minimalist aesthetic
    ''',
    config=types.VideoGenerationConfig(
        resolution='1080p',
        aspect_ratio='1:1'
    )
)

response = client.models.generate_video(
    model='veo-3.1-fast-generate-preview',
    prompt='''
    Trendy social media clip:
    - Text overlay "NEW ARRIVAL" appears
    - Fashion product showcase
    - Quick cuts and dynamic camera
    - Vibrant colors, high energy
    - Upbeat pacing
    ''',
    config=types.VideoGenerationConfig(
        resolution='1080p',
        aspect_ratio='9:16'  # Mobile
    )
)

3. Explainer Animations

response = client.models.generate_video(
    model='veo-3.1-generate-preview',
    prompt='''
    Educational animation:
    - Simple diagram illustrating data flow
    - Arrows and icons animating in sequence
    - Clean, clear visual hierarchy
    - Smooth transitions between steps
    - Professional corporate style
    ''',
    config=types.VideoGenerationConfig(
        resolution='720p',
        aspect_ratio='16:9'
    )
)

Safety & Content Policy

Safety Settings

config = types.VideoGenerationConfig(
    safety_settings=[
        types.SafetySetting(
            category=types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
            threshold=types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE
        )
    ]
)

Prohibited Content

Violence, gore, harm
Sexually explicit content
Hate speech, harassment
Copyrighted characters/brands
Real people (without consent)
Misleading/deceptive content

Limitations

Duration: Fixed 8 seconds (as of Sept 2025)
Frame Rate: 24fps only
File Size: ~5-20MB per video
Generation Time: 30s-2min depending on resolution
Reference Images: Max 3 images
Preview Status: API may change (3.1 models)
Audio: Cannot upload custom audio (native only)
No real-time: Pre-generation required

Troubleshooting

Long Generation Times

import time

# Track generation progress
start = time.time()
response = client.models.generate_video(...)
duration = time.time() - start
print(f"Generated in {duration:.1f}s")

Expected times:

Fast models + 720p: 30-45s
Standard models + 720p: 45-90s
Fast models + 1080p: 45-60s
Standard models + 1080p: 60-120s

Safety Filter Blocking

try:
    response = client.models.generate_video(...)
except Exception as e:
    if 'safety' in str(e).lower():
        print("Video blocked by safety filters")
        # Modify prompt and retry

Quota Exceeded

# Implement exponential backoff
import time

def generate_with_retry(model, prompt, max_retries=3):
    for attempt in range(max_retries):
        try:
            return client.models.generate_video(model=model, prompt=prompt)
        except Exception as e:
            if '429' in str(e):  # Rate limit
                wait = 2 ** attempt
                print(f"Rate limited, waiting {wait}s...")
                time.sleep(wait)
            else:
                raise
    raise Exception("Max retries exceeded")

Cost Estimation

Pricing: TBD (preview models)

Estimated based on compute:

Fast + 720p: ~$0.05-$0.10 per video
Standard + 1080p: ~$0.15-$0.25 per video

Monitor: https://ai.google.dev/pricing

Resources

Current: Video Generation

Related Capabilities:

Video Analysis - Understanding existing videos
Image Generation - Creating static images
Image Understanding - Analyzing reference images

Back to: AI Multimodal Skill

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