Stable Video 4D (SV4D)
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Stability AI,Northeastern University
- Organisation type
- Industry,Academia
- Country
- United Kingdom of Great Britain and Northern Ireland, United States of America
- Published
- 24 July 2024
- Authors
- Yiming Xie, Chun-Han Yao, Vikram Voleti, Huaizu Jiang, Varun Jampani
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision, Video, 3D modeling
- Task
- 3D reconstruction
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA H100 SXM5 80GB
- Chips used
- 8
- Power draw
- 11.0 kW
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Open — downloadable
- Model access
- Open weights (restricted use)
- Training code
- Unreleased
- Hugging Face
- stabilityai
Community License: Free for research, non-commercial, and commercial use by organizations and individuals generating annual revenue of US $1,000,000 (or local currency equivalent) or less, regardless of the source of that revenue. https://huggingface.co/stabilityai/sv4d
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency
- Last updated
- 11 February 2026
What the numbers mean
What this model is
Stable Video 4D (SV4D) was published by Stability AI,Northeastern University, in the country recorded as United Kingdom of Great Britain and Northern Ireland, during July 2024. The publishing organisation is categorised as industry,Academia.
It works in the domain of Vision, Video, 3D modeling, and is recorded as performing the task of 3D reconstruction.
Because its weights were released, nothing about running it depends on a provider staying available — it is yours once downloaded. On Hugging Face it is published under the organisation stabilityai.
Answers
Stable Video 4D (SV4D) — common questions
Stable Video 4D (SV4D)— what GPU do I need to run it?
We cannot say. It has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
Stable Video 4D (SV4D)— is it open source?
Its weights are published, so it can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
Stable Video 4D (SV4D)— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Stable Video 4D (SV4D)— who created it?
It was published by Stability AI,Northeastern University, based in United Kingdom of Great Britain and Northern Ireland, an organisation categorised as industry,Academia.
Stable Video 4D (SV4D)— when was it released?
It was published in July 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Stable Video 4D (SV4D)— what is it used for?
It works in the domain of Vision, Video, 3D modeling, and is recorded as handling the task of 3D reconstruction. These are the areas it was designed around; they describe intent rather than a hard boundary.
Stable Video 4D (SV4D)— where can I download it?
Its weights are published on Hugging Face, under the organisation stabilityai. We do not host model files — this site calculates what hardware is needed to run them.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.