Text to Video
Generate videos from text descriptions. The frontier of generative AI for content creation.
How Text to Video Works
A technical deep-dive into video generation. From diffusion models to Sora and beyond.
Generation Approaches
Three main paradigms for generating video from text.
Temporal Diffusion
Extend image diffusion to video
Diffusion Transformer (DiT)
Transformer-based diffusion
Autoregressive
Generate frame by frame
Diffusion Transformer (Sora-style)
Sora treats video as spacetime patches, enabling long, coherent generation.
Model Evolution
The rapid evolution of video generation models.
Key Challenges
What makes video generation hard.
API Comparison
Available video generation APIs.
| Model | Company | Duration | Resolution | Price | Access |
|---|---|---|---|---|---|
| Sora | OpenAI | 60s | 1080p | $$$ | Limited |
| Runway Gen-3 | Runway | 10s | 1080p | $$ | Open |
| Pika 2.0 | Pika | 4s | 1080p | $ | Open |
| Kling | Kuaishou | 120s | 1080p | $ | Open |
| Luma Dream Machine | Luma | 5s | 720p | $ | Open |
Code Examples
Get started with video generation.
import runwayml
# Initialize Runway client
client = runwayml.RunwayML()
# Generate video from text
task = client.image_to_video.create(
model='gen3a_turbo',
prompt_image='input.jpg', # Optional: image-to-video
prompt_text='A serene lake at sunset with gentle ripples',
duration=10, # seconds
ratio='16:9'
)
# Poll for completion
import time
while task.status not in ['SUCCEEDED', 'FAILED']:
time.sleep(10)
task = client.tasks.retrieve(task.id)
# Download result
if task.status == 'SUCCEEDED':
video_url = task.output[0]
# Download video from URLQuick Reference
- - Sora (limited access)
- - Veo 2 (Google)
- - Runway Gen-3
- - Pika 2.0
- - Luma Dream Machine
- - CogVideoX
- - Stable Video Diffusion
- - Open-Sora
Use Cases
- ✓Marketing content
- ✓Storyboarding
- ✓Synthetic training data
- ✓Creative exploration
Architectural Patterns
Latent Video Diffusion
Extend image diffusion to video with temporal layers.
- +High quality
- +Leverages image diffusion advances
- -Slow generation
- -VRAM intensive
Autoregressive Video
Generate frames sequentially as tokens.
- +Long videos possible
- +Controllable
- -Quality still developing
- -Slow
Image-to-Video
Animate a generated or given image.
- +More controllable
- +Can use existing images
- -Limited motion
- -First frame dependency
Implementations
API Services
Sora
OpenAIState-of-the-art quality. Up to 1 minute videos.
Runway Gen-3
RunwayProduction-ready. Good motion, 10 second clips.
Kling
KuaishouStrong motion coherence. Up to 2 minutes.
Open Source
Benchmarks
Quick Facts
- Input
- Text
- Output
- Video
- Implementations
- 2 open source, 3 API
- Patterns
- 3 approaches