Nemotron 3 Super
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
- Organisation type
- Industry
- Country
- United States of America
- Published
- 11 March 2026
- Authors
- Aaron Blakeman, Aaron Grattafiori, Aarti Basant, Abhibha Gupta, Abhinav Khattar, Adi Renduchintala, Aditya Vavre, Akanksha Shukla, Akhiad Bercovich, Aleksander Ficek, Aleksandr Shaposhnikov, Alex Kondratenko, Alexander Bukharin, Alexandre Milesi, Ali Taghibakhshi, Alisa Liu, Amelia Barton, Ameya Sunil Mahabaleshwarkar, Amir Klein, Amit Zuker, Amnon Geifman, Amy Shen, Anahita Bhiwandiwalla, Andrew …
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation, Coding
- Numerical format
- NVFP4
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.
- Parameters
- 120B
- Training data
- tokens
"The new Super model is a 120B total, 12B active-parameter"
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Discretionary
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- Introducing Nemotron 3 Super: An Open Hybrid Mamba-Transformer MoE for Agentic Reasoning
- Last updated
- 10 April 2026
What the numbers mean
What this model is
Nemotron 3 Super was published by NVIDIA, in the country recorded as United States of America, during March 2026. The publishing organisation is categorised as industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation, Coding.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
The reason it appears in this catalogue at all: discretionary.
Answers
Nemotron 3 Super — common questions
Nemotron 3 Super— 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.
Nemotron 3 Super— how many parameters does it have?
It has a parameter count of 120B. "The new Super model is a 120B total, 12B active-parameter". That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Nemotron 3 Super— who created it?
It was published by NVIDIA, based in United States of America, an organisation categorised as industry.
Nemotron 3 Super— when was it released?
It was published in March 2026.
Nemotron 3 Super— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling/generation, Coding. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Nemotron 3 Super— 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.
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.