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Stable Video Diffusion (SVD, 14 frames)
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Stable Video Diffusion (SVD, 14 frames) is an open-weights video model from Stability AI, released November 2023. Its published size is 1.52B parameters. Licence: stable-video-diffusion-community.
Catalogue identity notes
Image-to-video model requiring a starting image; not text-to-video. Original release, distinct from SVD XT 1.1. Place a starting image at input.png. CUDA GPU plus system RAM required for CPU offload. 8GB VRAM is a planning estimate based on the documented chunking/offload setup; not a local measurement.
Model information sources
Video UNet only: HF Hub safetensors total for the official repo (pinned revision), 1,524,623,082 = unet/diffusion_pytorch_model.safetensors. The CLIP image encoder (632.1M) and the VAE (97.7M) are not included. Observed 2026-10-07.
$ how it compares
Scored video models released closest to Stable Video Diffusion (SVD, 14 frames), out of 139 with a score.
| # | model | score | where |
|---|---|---|---|
| 118 | 34±2 | local | |
| 120 | 32±3 | comparison only | |
| 127 | 27±2 | local | |
| 133 | 26±2 | local | |
| 134 | 25±2 | local |
$ where to run it
Other ways to run it
- Run it as published · needs ~8 GB, NVIDIA only · from huggingface.co/docs
uv run --with torch --with diffusers --with transformers --with accelerate --with imageio-ffmpeg python -c "import torch; from diffusers import StableVideoDiffusionPipeline; from diffusers.utils import load_image, export_to_video; p=StableVideoDiffusionPipeline.from_pretrained('stabilityai/stable-video-diffusion-img2vid', torch_dtype=torch.float16, variant='fp16'); p.enable_model_cpu_offload(); p.unet.enable_forward_chunking(); image=load_image('input.png').resize((1024,576)); frames=p(image, num_frames=14, decode_chunk_size=2).frames[0]; export_to_video(frames, 'video.mp4', fps=7)"
Official weights and documentation: huggingface.co/stabilityai ↗
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