Quiet-STaR
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
- Stanford University
- Organisation type
- Academia
- Country
- United States of America
- Published
- 14 March 2024
- Authors
- Eric Zelikman, Georges Harik, Yijia Shao, Varuna Jayasiri, Nick Haber, Noah D. Goodman
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
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
- 11.1 kW
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
- Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
- Last updated
- 28 November 2025
What the numbers mean
About this model
Quiet-STaR was published by Stanford University, in United States of America, in March 2024. It comes out of academia.
It works in Language.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
Quiet-STaR — common questions
What GPU do I need to run Quiet-STaR?
None. Quiet-STaR 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.
Is Quiet-STaR open source?
The licensing for Quiet-STaR was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Quiet-STaR have?
No parameter count has been published for Quiet-STaR, which is why no memory or speed figure appears on this page.
Who created Quiet-STaR?
Quiet-STaR was published by Stanford University, based in United States of America, categorised as academia.
When was Quiet-STaR released?
Quiet-STaR was published in March 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.
What is Quiet-STaR used for?
Quiet-STaR works in Language. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
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.