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Phenaki is a model capable of generating realistic videos from textual prompts, with the ability to change prompts over time and create videos of any desired length. It uses a tokenizer with causal attention in time to compress videos into discrete tokens, and a bidirectional masked transformer to generate video tokens from text. Phenaki can generate videos conditioned on a sequence of prompts, making it the first model to study video generation from time variable prompts. It outperforms previous video generation methods in terms of spatio-temporal quality and token count per video.


  • Generates videos from textual prompts
  • Allows for dynamic prompts that can change over time
  • Can generate videos of any desired length

Use Cases

  • Creating videos from text descriptions
  • Generating videos for storytelling or visualization purposes
  • Producing video content based on textual prompts

Suited For

  • Content creators and storytellers
  • Researchers in the field of video generation
  • Anyone interested in generating videos from text prompts


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