AI models
Diffusion Renderer
Parameters
1.1B
Published
Mar 22, 2025
Diffusion Renderer is an AI model developed by NVIDIA, University of Toronto, Vector Institute and University of Illinois Urbana-Champaign (UIUC) (United States and Canada), first published in March 2025. It works in the video domain, on tasks such as video editing, video-to-video and 3d segmentation.
Epoch AI has no training-compute estimate for this model. The model has 1,100,000,000 parameters. Training ran on 32 NVIDIA A100 for about 48 hours.
Access: Open weights (non-commercial). Its weights are openly available. It is built on top of Stable Video Diffusion. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- NVIDIA, University of Toronto, Vector Institute, University of Illinois Urbana-Champaign (UIUC)
- Country of organization
- United States, Canada
- Domain
- Video
- Task
- Video editing, Video-to-video, 3D segmentation
- Compute estimation method
- Hardware
- Parameters
- 1,100,000,000
- Training hardware
- NVIDIA A100
- Chips used
- 32
- Training time
- 48 h
- Training power draw
- 25.1 kW
- Numerical format
- FP16
- Model accessibility
- Open weights (non-commercial)
- Open weights
- Yes
- Base model
- Stable Video Diffusion
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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