CALM (NVIDIA)
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
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,Technion - Israel Institute of Technology
- Organisation type
- Industry,Academia
- Country
- United States of America, Israel
- Published
- 6 August 2023
- Authors
- Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Robotics
- Task
- Animal (human/non-human) imitation
- Approach
- Reinforcement learning
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 A100
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Likely above 10²³ FLOP
- Yes
- Record confidence
- Unknown
- Citations
- 122
Sources
Where this record came from and when it was last checked.
- Reference
- CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
- Last updated
- 13 August 2026
What the numbers mean
Background
CALM (NVIDIA) was published by NVIDIA,Technion - Israel Institute of Technology, in the country recorded as United States of America, during August 2023. The category the publisher falls under is industry,Academia.
It works in the domain of Robotics, and is recorded as performing the task of animal (human/non-human) imitation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
CALM (NVIDIA) — common questions
CALM (NVIDIA)— who created it?
It was published by NVIDIA,Technion - Israel Institute of Technology, based in United States of America, an organisation categorised as industry,Academia.
CALM (NVIDIA)— when was it released?
It was published in August 2023. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
CALM (NVIDIA)— what is it used for?
It works in the domain of Robotics, and is recorded as handling the task of animal (human/non-human) imitation. These are the areas it was designed around; they describe intent rather than a hard boundary.
CALM (NVIDIA)— what GPU do I need to run it?
None. This is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
CALM (NVIDIA)— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
CALM (NVIDIA)— 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.
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.