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Stable Video Diffusion
Model Family Report
Compatible Apps
Generate images and videos using a powerful low-level workflow graph builder - the fastest, most flexible, and most advanced visual generation UI.
Browse Models
Generate images and videos using a powerful low-level workflow graph builder - the fastest, most flexible, and most advanced visual generation UI.
The Stable Video Diffusion (SVD) family represents a comprehensive suite of AI models developed by Stability AI for video generation and 3D content creation. Starting with the release of Stable Video Diffusion in November 2023, this family has rapidly evolved to include specialized models for video generation, 3D reconstruction, and novel view synthesis.
The model family began with the release of Stable Video Diffusion and its extended variant SVD-XT in November 2023. These initial models focused on converting static images into short video clips, with SVD generating 14 frames and SVD-XT producing 25 frames at 576x1024 resolution. The technology built upon Stability AI's successful Stable Diffusion image model, incorporating temporal convolution and attention layers for video generation.
In February 2024, Stability AI released SVD-XT 1.1, an improved version optimized for output consistency at 6FPS. This update maintained the core capabilities while enhancing the quality and reliability of generated content. The progression continued with Stable Video 3D in March 2024, which introduced specialized capabilities for creating orbital videos from single images, representing a significant step toward 3D content generation.
July 2024 marked the introduction of Stable Video 4D, which unified video generation and novel view synthesis into a single model. This advancement enabled the creation of multiple novel-view videos from a single input video, representing a significant leap in dynamic 3D content generation capabilities. In August 2024, the family expanded to include Stable Fast 3D, focusing on rapid 3D reconstruction from single images with enhanced efficiency and reduced computational requirements.
The model family shares several foundational technical characteristics, including the use of latent diffusion architecture derived from Stable Diffusion 2.1. All models incorporate temporal convolution and attention layers, though their specific implementations vary based on intended use cases. The training process typically involves three stages: text-to-image pretraining, video pretraining on large datasets, and high-quality video fine-tuning on curated clips.
Data curation has played a crucial role across the family's development, with sophisticated processes including cut detection, motion annotation, caption generation, and aesthetics scoring. The models utilize specialized decoders for ensuring temporal consistency, with the f8-decoder being particularly important for maintaining visual coherence across frames.
The SVD family demonstrates a broad range of capabilities, from basic video generation to complex 3D reconstruction. Early models focused on image-to-video conversion with customizable frame rates and camera motions. Later additions expanded into 3D content generation, with SV3D enabling orbital video creation and SV4D introducing novel view synthesis capabilities.
The family's applications span various fields, including:
Throughout the family, certain limitations persist, including restrictions on video length (typically 4 seconds or less), challenges with photorealistic rendering, and difficulties with text and face generation. The models are explicitly not designed for generating factually accurate representations of people or events, as outlined in Stability AI's Acceptable Use Policy.
The computational requirements vary significantly across the family, from the resource-intensive early models requiring A100 GPUs to more recent optimizations like Stable Fast 3D, which can operate on consumer-grade hardware. Environmental impact considerations have also been documented, with training processes generating substantial CO2 emissions.
All models in the family are released under variations of the Stability AI Community License, which generally permits research and limited commercial use. Commercial applications for organizations with annual revenue exceeding $1 million require separate licensing arrangements through Stability AI. The complete source code and model implementations are available through the official Stability AI GitHub repository.
The rapid evolution of the Stable Video Diffusion family suggests continued development in areas such as longer video generation, improved photorealism, and more efficient 3D reconstruction capabilities. The progression from basic video generation to complex 4D content creation indicates a trend toward more sophisticated and integrated multimedia generation capabilities.