What are Open Source Video Models for Film Pre-Visualization?
Open source video models for film pre-visualization are specialized AI systems that generate cinematic video sequences from text descriptions or static images. These models use advanced deep learning architectures like Mixture-of-Experts (MoE) and diffusion transformers to create smooth, natural video content that helps filmmakers visualize scenes before production. They enable directors and cinematographers to experiment with lighting, composition, camera movements, and complex motion dynamics, democratizing access to powerful pre-visualization tools that were once exclusive to major studios.
Wan-AI/Wan2.2-T2V-A14B
Wan2.2-T2V-A14B is the industry's first open-source video generation model with a Mixture-of-Experts (MoE) architecture, released by Alibaba. This model focuses on text-to-video generation, capable of producing 5-second videos at both 480P and 720P resolutions with meticulously curated aesthetic data for precise cinematic style control.
Wan-AI/Wan2.2-T2V-A14B: Revolutionary Text-to-Video Generation
Wan2.2-T2V-A14B is the industry's first open-source video generation model with a Mixture-of-Experts (MoE) architecture, released by Alibaba. This model focuses on text-to-video (T2V) generation, capable of producing 5-second videos at both 480P and 720P resolutions. By introducing an MoE architecture, it expands the total model capacity while keeping inference costs nearly unchanged; it features a high-noise expert for the early stages to handle the overall layout and a low-noise expert for later stages to refine video details. Furthermore, Wan2.2 incorporates meticulously curated aesthetic data with detailed labels for lighting, composition, and color, allowing for more precise and controllable generation of cinematic styles. Compared to its predecessor, the model was trained on significantly larger datasets, which notably enhances its generalization across motion, semantics, and aesthetics, enabling better handling of complex dynamic effects.
Pros
- Industry's first open-source MoE video generation model.
- Produces videos at both 480P and 720P resolutions.
- Curated aesthetic data for cinematic style control.
Cons
- Limited to 5-second video duration.
- Requires understanding of prompt engineering for optimal results.
Why We Love It
- It pioneers open-source cinematic video generation with precise lighting, composition, and color control—perfect for film pre-visualization workflows.
Wan-AI/Wan2.2-I2V-A14B
Wan2.2-I2V-A14B is one of the industry's first open-source image-to-video generation models featuring a Mixture-of-Experts architecture. It specializes in transforming static images into smooth, natural video sequences with improved motion stability and reduced unrealistic camera movements.
Wan-AI/Wan2.2-I2V-A14B: Advanced Image-to-Video Transformation
Wan2.2-I2V-A14B is one of the industry's first open-source image-to-video generation models featuring a Mixture-of-Experts (MoE) architecture, released by Alibaba's AI initiative, Wan-AI. The model specializes in transforming a static image into a smooth, natural video sequence based on a text prompt. Its key innovation is the MoE architecture, which employs a high-noise expert for the initial video layout and a low-noise expert to refine details in later stages, enhancing model performance without increasing inference costs. Compared to its predecessors, Wan2.2 was trained on a significantly larger dataset, which notably improves its ability to handle complex motion, aesthetics, and semantics, resulting in more stable videos with reduced unrealistic camera movements.
Pros
- First open-source image-to-video model with MoE architecture.
- Excellent motion stability with reduced unrealistic movements.
- Enhanced performance without increased inference costs.
Cons
- Requires high-quality input images for best results.
- May need technical expertise for optimal prompt crafting.
Why We Love It
- It transforms static concept art into dynamic video sequences with exceptional stability, making it ideal for film pre-visualization and storyboard animation.
Wan-AI/Wan2.1-I2V-14B-720P-Turbo
Wan2.1-I2V-14B-720P-Turbo is the TeaCache accelerated version that reduces video generation time by 30%. This 14B parameter model generates 720P high-definition videos using diffusion transformer architecture with innovative spatiotemporal VAE technology.
Wan-AI/Wan2.1-I2V-14B-720P-Turbo: High-Speed HD Video Generation
Wan2.1-I2V-14B-720P-Turbo is the TeaCache accelerated version of the Wan2.1-I2V-14B-720P model, reducing single video generation time by 30%. Wan2.1-I2V-14B-720P is an open-source advanced image-to-video generation model, part of the Wan2.1 video foundation model suite. This 14B model can generate 720P high-definition videos. And after thousands of rounds of human evaluation, this model is reaching state-of-the-art performance levels. It utilizes a diffusion transformer architecture and enhances generation capabilities through innovative spatiotemporal variational autoencoders (VAE), scalable training strategies, and large-scale data construction. The model also understands and processes both Chinese and English text, providing powerful support for video generation tasks.
Pros
- 30% faster generation with TeaCache acceleration.
- Generates 720P high-definition video output.
- State-of-the-art performance validated through human evaluation.
Cons
- Higher computational requirements for 720P generation.
- Focused primarily on image-to-video, not text-to-video.
Why We Love It
- It delivers professional-grade 720P video generation with exceptional speed, perfect for rapid film pre-visualization workflows where time and quality are crucial.
Video Model Comparison
In this table, we compare 2025's leading open-source video models for film pre-visualization, each with unique strengths. For text-based concept visualization, Wan2.2-T2V-A14B offers pioneering cinematic control. For storyboard animation, Wan2.2-I2V-A14B provides exceptional motion stability. For rapid HD pre-visualization, Wan2.1-I2V-720P-Turbo delivers speed and quality. This comparison helps filmmakers choose the right tool for their specific pre-visualization needs.
| Number | Model | Developer | Subtype | SiliconFlow Pricing | Core Strength |
|---|---|---|---|---|---|
| 1 | Wan-AI/Wan2.2-T2V-A14B | Wan | Text-to-Video | $0.29/Video | Cinematic style control |
| 2 | Wan-AI/Wan2.2-I2V-A14B | Wan | Image-to-Video | $0.29/Video | Superior motion stability |
| 3 | Wan-AI/Wan2.1-I2V-14B-720P-Turbo | Wan | Image-to-Video | $0.21/Video | 30% faster HD generation |
Frequently Asked Questions
Our top three picks for 2025 are Wan-AI/Wan2.2-T2V-A14B, Wan-AI/Wan2.2-I2V-A14B, and Wan-AI/Wan2.1-I2V-14B-720P-Turbo. Each model excelled in different aspects of film pre-visualization: cinematic style control, motion stability, and high-definition speed generation respectively.
For concept-to-video creation from scripts, Wan2.2-T2V-A14B excels with its cinematic style controls. For animating storyboards and concept art, Wan2.2-I2V-A14B offers the best motion stability. For rapid HD pre-visualization where speed is crucial, Wan2.1-I2V-720P-Turbo provides 30% faster generation while maintaining quality.