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bytedance / seedance-1-lite

A video generation model that offers text-to-video and image-to-video support for 5s or 10s videos, at 480p and 720p resolution

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Seedance 1.0

A video generation model that creates videos from text prompts and images.

Core Capabilities

Video Generation

  • Text-to-Video (T2V): Generate videos from text descriptions
  • Image-to-Video (I2V): Generate videos from static images with optional text prompts
  • Resolution: Outputs 1080p videos

Motion and Dynamics

  • Wide dynamic range supporting both subtle and large-scale movements
  • Maintains physical realism and stability across motion sequences
  • Handles complex action sequences and multi-agent interactions

Multi-Shot Support

  • Native multi-shot video generation with narrative coherence
  • Maintains consistency in subjects, visual style, and atmosphere across shot transitions
  • Handles temporal and spatial shifts between scenes

Style and Aesthetics

  • Supports diverse visual styles: photorealism, cyberpunk, illustration, felt texture, and others
  • Interprets stylistic prompts accurately
  • Maintains cinematic quality with rich visual details

Prompt Understanding

  • Parses natural language descriptions effectively
  • Stable control over camera movements and positioning
  • Accurate interpretation of complex scene descriptions
  • Strong prompt adherence across generated content

Technical Specifications

  • Model Version: 1.0
  • Output Resolution: 1080p
  • Input Types: Text prompts, images (for I2V mode)
  • Video Length: Multi-shot capable (specific duration limits not specified)

Model Performance

Based on internal benchmarks using SeedVideoBench-1.0 and third-party evaluations:

  • High scores in prompt adherence
  • Strong motion quality ratings
  • Competitive aesthetic quality
  • Effective source image consistency in I2V tasks

Use Cases

  • Creative video content generation
  • Prototype development for film and animation
  • Commercial video production
  • Educational and documentary content
  • Fantasy and surreal video creation

Limitations

  • Performance metrics based on specific benchmark datasets
  • Actual generation quality may vary with prompt complexity
  • Multi-shot consistency depends on prompt clarity and scene descriptions