Wan2.1-I2V-14B-720P
| Property | Value |
|---|---|
| Model Size | 14B parameters |
| Resolution Support | 720P HD |
| License | Apache 2.0 |
| Framework | Diffusion Transformer |
| Architecture | 5120 dimension, 40 layers, 40 attention heads |
What is Wan2.1-I2V-14B-720P?
Wan2.1-I2V-14B-720P is a state-of-the-art image-to-video generation model that represents a significant advancement in video synthesis technology. As part of the Wan2.1 suite, this model specializes in converting still images into high-quality 720P videos while maintaining temporal consistency and visual fidelity.
Implementation Details
The model utilizes a sophisticated architecture based on Diffusion Transformers with a novel 3D causal VAE design. It features a dimension of 5120, 40 transformer layers, and 40 attention heads, enabling efficient processing of high-resolution video content. The implementation includes both single-GPU and multi-GPU support through FSDP + xDiT USP technology.
- Advanced spatio-temporal variational autoencoder (Wan-VAE)
- Flow Matching framework integration
- T5 Encoder for multilingual text processing
- Shared MLP across transformer blocks for time embedding processing
Core Capabilities
- 720P high-definition video generation
- Support for both local and remote prompt extension
- Multi-GPU parallel processing
- Efficient memory management with peak performance
- Compatibility with various inference methods
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its ability to generate high-quality 720P videos from still images while outperforming both open-source and closed-source alternatives in extensive manual evaluations. It incorporates a novel VAE architecture capable of processing unlimited-length 1080P videos.
Q: What are the recommended use cases?
The model is ideal for professional video content creation, image animation, and high-quality video synthesis applications where resolution and temporal consistency are crucial. It's particularly well-suited for scenarios requiring the transformation of still images into dynamic, high-definition video content.
