Wan | 2.5 | Preview | Text to Video

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WAN-2.5

Wan 2.5 Preview is a model designed to generate realistic videos directly from text. It transforms short descriptions into cinematic visuals with natural motion, smooth camera work, and high-quality output. The “Preview” version is optimized for quick tests and experiments, making it easy to visualize ideas before moving into full production.

Avg Run Time: 180.000s

Model Slug: wan-2-5-preview-text-to-video

Playground

Input

Enter a URL or choose a file from your computer.

Output

Example Result

Preview and download your result.

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API & SDK

Create a Prediction

Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.

Get Prediction Result

Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.

Readme

Table of Contents
Overview
Technical Specifications
Key Considerations
Tips & Tricks
Capabilities
What Can I Use It For?
Things to Be Aware Of
Limitations

Overview

Wan 2.5 Preview is an advanced AI model developed by Alibaba Cloud, designed to transform text into realistic videos with high-quality visuals and synchronized audio. It is part of a broader suite of AI video generation tools that have been evolving to meet the needs of content creators, advertisers, and filmmakers. The model is notable for its ability to generate photorealistic videos with smooth motion and clear audio, making it suitable for a variety of applications, including storytelling, advertising, and creative projects.

One of the key features of Wan 2.5 is its ability to handle complex prompts with high accuracy, combining advanced natural language understanding with visual reasoning. This allows for precise control over dialogue, style, and camera work, ensuring outputs that are coherent and faithful to creative instructions. The model supports resolutions up to 1080p and operates at a frame rate of 24 frames per second, providing stable dynamic performance and richer temporal-spatial detail.

The underlying architecture of Wan 2.5 involves a 'Pose-Latent Transformer' focused on enhanced character expression and temporal motion control algorithms. This architecture effectively addresses common AI video issues such as character stiffness and rigid movements, resulting in more natural motion and character integrity.

Technical Specifications

  • Architecture: Pose-Latent Transformer
  • Parameters: Not specified in available sources
  • Resolution: Supports up to 1080p
  • Input/Output formats: Text-to-video, image-to-video
  • Performance metrics: Not explicitly detailed in available sources

Key Considerations

  • Prompt Accuracy: Ensure that prompts are clear and specific to achieve desired results.
  • Style Adaptation: Wan 2.5 can adapt across various styles, but consistency may vary depending on the complexity of the prompt.
  • Resource Efficiency: The model is optimized for efficient output, but resource requirements can vary based on the complexity of the video generated.
  • Quality vs Speed Trade-offs: Higher quality outputs may require more processing time.
  • Prompt Engineering Tips: Use detailed descriptions and specify desired styles or genres for better results.

Tips & Tricks

  • Optimal Parameter Settings: Experiment with different prompt structures to find what works best for your specific use case.
  • Prompt Structuring Advice: Include specific details about desired visuals, audio, and style to enhance output quality.
  • Iterative Refinement Strategies: Start with simple prompts and refine them based on initial results.
  • Advanced Techniques: Use Wan 2.5 to generate music videos by specifying rhythm and sound synchronization in prompts.

Capabilities

  • Native Audio Generation: Wan 2.5 can generate synchronized audio, including dialogues, ambient sounds, and background music.
  • Style Adaptation: Seamlessly adapts across cinematic, anime, and illustration styles.
  • High-Quality Outputs: Produces videos with clear details and smooth motion.
  • Versatility: Suitable for storytelling, advertising, creative projects, and more.
  • Technical Strengths: Offers strong prompt adherence and visual reasoning capabilities.

What Can I Use It For?

  • Professional Applications: Ideal for creating short films, social media ads, and branded content.
  • Creative Projects: Useful for music videos, animated clips, and character animations.
  • Business Use Cases: Effective for fast-moving marketing campaigns requiring high-quality video content.
  • Personal Projects: Suitable for experimenting with different styles and storytelling techniques.

Things to Be Aware Of

  • Experimental Features: The "Preview" version is optimized for quick tests and may have limitations compared to full versions.
  • Known Quirks: Some users report occasional inconsistencies in audio-visual synchronization.
  • Performance Considerations: Resource requirements can vary based on video complexity.
  • Consistency Factors: Outputs may vary slightly in quality depending on prompt clarity and complexity.
  • Positive Feedback Themes: Users appreciate the model's ability to generate high-quality visuals and synchronized audio.

Limitations

  • Video Duration: Limited to generating videos up to 10 seconds in length.
  • Technical Constraints: May require significant computational resources for complex video generation tasks.
  • Style Consistency: While adaptable across styles, maintaining consistency can be challenging with very complex or abstract prompts.