What are Open Source Text-to-Video AI Models?
Open source text-to-video AI models are specialized deep learning systems that generate high-quality video sequences from text descriptions or transform static images into dynamic video content. Using advanced architectures like diffusion transformers and Mixture-of-Experts (MoE), they translate natural language prompts into smooth, natural video sequences. This technology allows developers and creators to generate, modify, and build upon video content with unprecedented freedom. They foster collaboration, accelerate innovation, and democratize access to powerful video creation tools, enabling a wide range of applications from digital storytelling to large-scale enterprise video production.
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 (T2V) generation, capable of producing 5-second videos at both 480P and 720P resolutions. The MoE architecture expands total model capacity while keeping inference costs nearly unchanged, featuring specialized experts for different stages of video generation.
Wan-AI/Wan2.2-T2V-A14B: Revolutionary MoE Architecture for Text-to-Video
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.
- Supports both 480P and 720P resolution output.
- Precise cinematic style control with aesthetic data.
Cons
- Limited to 5-second video generation.
- May require technical expertise for optimal prompt crafting.
Why We Love It
- It pioneers the MoE architecture in open-source video generation, delivering cinematic quality with precise control over lighting, composition, and visual aesthetics.
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 (MoE) architecture. The model specializes in transforming static images into smooth, natural video sequences based on text prompts, with innovative dual-expert architecture for optimal layout and detail refinement.
Wan-AI/Wan2.2-I2V-A14B: Advanced Image-to-Video with MoE Innovation
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
- Industry-leading MoE architecture for image-to-video.
- Dual-expert system for layout and detail optimization.
- Improved motion stability and reduced camera artifacts.
Cons
- Requires input image for video generation.
- Performance depends heavily on input image quality.
Why We Love It
- It transforms static images into cinematic videos with unprecedented stability and motion realism, making it perfect for bringing artwork and photography to life.
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 variational autoencoders (VAE), reaching state-of-the-art performance levels through thousands of human evaluations.
Wan-AI/Wan2.1-I2V-14B-720P-Turbo: High-Speed 720P 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.
- 720P high-definition video output quality.
- State-of-the-art performance validated by human evaluation.
Cons
- Lower output price requires careful cost management.
- Requires significant computational resources for 720P output.
Why We Love It
- It delivers the perfect balance of speed and quality, generating 720P videos 30% faster while maintaining state-of-the-art performance standards.
AI Video Model Comparison
In this table, we compare 2025's leading open-source text-to-video AI models, each with unique strengths. For pure text-to-video creation, Wan2.2-T2V-A14B offers revolutionary MoE architecture. For transforming images into videos, Wan2.2-I2V-A14B provides advanced motion stability. For high-speed 720P generation, Wan2.1-I2V-14B-720P-Turbo delivers optimal performance. This side-by-side view helps you choose the right tool for your specific video generation needs.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | Wan-AI/Wan2.2-T2V-A14B | Wan-AI | Text-to-Video | $0.29/Video | First open-source MoE architecture |
| 2 | Wan-AI/Wan2.2-I2V-A14B | Wan-AI | Image-to-Video | $0.29/Video | Advanced motion stability & realism |
| 3 | Wan-AI/Wan2.1-I2V-14B-720P-Turbo | Wan-AI | Image-to-Video | $0.21/Video | 30% faster 720P 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 of these models stood out for their innovation, performance, and unique approach to solving challenges in text-to-video synthesis and image-to-video generation.
For pure text-to-video generation, Wan2.2-T2V-A14B leads with its revolutionary MoE architecture and cinematic style control. For image-to-video tasks, both Wan2.2-I2V-A14B offers superior motion stability, while Wan2.1-I2V-14B-720P-Turbo provides the fastest 720P generation with 30% speed improvement.