SVD-XT
SVD-XT is an extended version of Stability AI's Stable Video Diffusion that generates 25-frame video sequences from single input images, doubling the output length compared to the base SVD model's 14 frames while maintaining visual quality and temporal coherence.
Key Highlights
Extended 25-Frame Video Generation
Generates 25 frames per video compared to the base SVD's 14 frames, producing approximately 6 seconds of smooth, temporally coherent animation from a single image
Motion Bucket Controllability
Adjustable motion bucket parameter lets users control animation intensity from subtle environmental shifts to dynamic scene movements with precision
High-Quality Image Fidelity Preservation
Maintains the visual style, colors, and details of the input image while adding natural motion through latent space processing and cross-attention conditioning
Foundation for Community Ecosystem
Serves as the architectural basis for numerous community extensions, fine-tuned variants, and creative workflow integrations across ComfyUI and other platforms
About
SVD-XT (Stable Video Diffusion Extended) is an image-to-video generation model developed by Stability AI that extends the base Stable Video Diffusion model to produce longer, more temporally coherent video sequences. Released in late 2023, SVD-XT generates 25 frames of video from a single input image at resolutions up to 576x1024, creating approximately 6 seconds of smooth animation at 4 frames per second. The extended frame count enables significantly smoother and more natural motion sequences compared to the base SVD model, with the difference being particularly noticeable in slow camera movements and environmental animations.
The model builds upon the Stable Diffusion image generation architecture by adding temporal convolution and attention layers that enable frame-to-frame consistency throughout the generated sequence. SVD-XT was trained on a large-scale video dataset curated by Stability AI, using a multi-stage training process that first pre-trained on images, then fine-tuned on video data to learn natural motion patterns from diverse sources. The extended version (XT) specifically improves upon the base SVD model by generating 25 frames instead of 14, providing longer and smoother video output. These additional frames allow motion to be expressed over a broader time span and enable the capture of more complex motion sequences.
A key feature of SVD-XT is its motion bucket parameter, which allows users to control the amount of motion in the generated video with precision. Lower motion bucket values produce subtle, gentle movements while higher values create more dynamic and dramatic motion. This controllability makes SVD-XT versatile across use cases ranging from gentle camera pans and subtle environmental animations to more active scene dynamics. Additional parameters for noise augmentation and fps provide further fine-tuning of the output's character and rhythm, and the combination of these parameters makes it possible to produce videos with very different atmospheres from the same input image.
The model operates in a latent space, encoding the input image through a VAE encoder, processing it through the temporal UNet with cross-attention to the image conditioning, and decoding the resulting latent frames back to pixel space. This approach maintains the visual quality and style of the input image while adding natural-looking motion seamlessly. The compression quality of the VAE directly impacts the visual detail level of the output video, and SVD-XT's VAE has been specifically optimized to preserve fine details during the encoding-decoding cycle. The latent space approach also improves memory efficiency, enabling the generation of longer video sequences.
SVD-XT is available under the Stability AI Community License for research and non-commercial use, with commercial licensing available separately for enterprise applications. It integrates with popular frameworks including ComfyUI and Hugging Face Diffusers, and has become a foundational component in many image-to-video workflows across the creative community. The model's architecture has also served as the basis for numerous community extensions and fine-tuned variants optimized for specific types of motion or visual styles, and these community contributions continuously expand the model's capabilities.
Practical applications include product photography animation, landscape and nature animation, social media content creation, web design animations, e-commerce visuals, and creative art projects. SVD-XT continues to strongly maintain its position as one of the standard reference models in open-source video generation, supported by accessible hardware requirements and a robust community ecosystem.
Use Cases
Product Photography Animation
Transform static product photos into engaging video content with subtle motion effects for e-commerce listings and social media marketing
Architectural Visualization
Animate architectural renders and interior design images with gentle camera movements to create immersive walkthrough-style presentations
Social Media Content Creation
Convert artwork, photographs, and illustrations into short animated clips that capture attention in social media feeds and stories
Digital Art and Illustration Animation
Bring digital paintings and illustrations to life with natural motion while preserving the original artistic style and color palette
Pros & Cons
Pros
- Extended version of Stable Video Diffusion — generation up to 25 frames
- Built on Stability AI's strong visual understanding infrastructure
- Released as open source to the research community
- Successful at simulating camera movements
Cons
- Image-to-video only — does not support text input
- Limited to 576x1024 resolution
- Blurring and morphing effects in complex movements
- Commercial license restrictions apply
Technical Details
Parameters
1.5B
License
Stability AI Community
Features
- Image-to-Video Generation
- Extended 25-Frame Output
- 576x1024 Resolution Support
- Stable Video Diffusion Architecture
- Temporal Layer Fine-Tuning
- Motion Bucket Control
- Open-Source Research Weights
- ComfyUI and Diffusers Integration
Benchmark Results
| Metric | Value | Compared To | Source |
|---|---|---|---|
| Parametre Sayısı | 1.5B | DynamiCrafter: 1.4B | Stability AI / SVD Paper |
| Kare Sayısı | 25 kare | SVD: 14 kare | SVD-XT Paper (arXiv:2311.15127) |
| Video Çözünürlüğü | 1024x576 | I2VGen-XL: 1280x720 | Stability AI / Hugging Face |
| FVD Skoru (UCF-101) | 242.02 | DynamiCrafter: ~290 | SVD Paper |
Available Platforms
Frequently Asked Questions
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