3DGUT
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
- NVIDIA,University of Toronto
- Organisation type
- Industry,Academia
- Country
- United States of America, Canada
- Published
- 24 March 2025
- Authors
- Qi Wu, Janick Martinez Esturo, Ashkan Mirzaei, Nicolas Moenne-Loccoz, Zan Gojcic
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- 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
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 (unrestricted)
- Training code
- Open source
Apache 2.0 https://github.com/nv-tlabs/3dgrut
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
- 3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting
- Last updated
- 28 November 2025
What the numbers mean
About this model
3DGUT was published by NVIDIA,University of Toronto, in United States of America, in March 2025. industry,Academia is the category the publisher falls under.
It works in 3D modeling, and is recorded as doing 3D reconstruction.
The weights are published, so it can be downloaded and run on your own hardware indefinitely, offline, with no account attached.
Answers
3DGUT — common questions
When was 3DGUT released?
3DGUT was published in March 2025.
What is 3DGUT used for?
3DGUT works in 3D modeling, and is recorded as handling 3D reconstruction. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Where can I download 3DGUT?
The weights for 3DGUT are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
What GPU do I need to run 3DGUT?
We cannot say. 3DGUT 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.
Is 3DGUT open source?
Its weights are published, so 3DGUT 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.
How many parameters does 3DGUT have?
No parameter count has been published for 3DGUT, which is why no memory or speed figure appears on this page.
Who created 3DGUT?
3DGUT was published by NVIDIA,University of Toronto, based in United States of America, categorised as industry,Academia.
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.