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Nemotron

Family of artificial intelligence models developed by Nvidia From Wikipedia, the free encyclopedia

Nemotron is a family of artificial intelligence models developed by Nvidia. It includes large language models and multimodal models intended for reasoning, computer programming, information retrieval and agentic AI applications. Nvidia has released open model weights, training data, software and training methods for parts of the family.[2][3]

ReleaseNovember 15, 2023; 2 years ago (2023-11-15)
LicenseVarious
Nvidia Open Model License[1]
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Nemotron
DeveloperNvidia
ReleaseNovember 15, 2023; 2 years ago (2023-11-15)
TypeLarge language model
LicenseVarious
Nvidia Open Model License[1]
Websitedeveloper.nvidia.com/topics/ai/nemotron
Repositorygithub.com/NVIDIA-NeMo/Nemotron
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History

Nvidia introduced the Nemotron-3 8B models in November 2023 for enterprise generative artificial intelligence applications.[4] Nemotron-4 340B followed in June 2024 and included base, instruction-tuned and reward models designed partly for generating synthetic data.[5]

Nvidia later introduced Llama Nemotron, a series of reasoning models derived from Meta's Llama models.[6] In December 2025, Nvidia announced the Nemotron 3 generation, beginning with Nemotron 3 Nano.[2] Nemotron 3 Super and Ultra were released in 2026.[7][8]

Models

More information Family, Released ...
Major model families
Family Released Purpose
Nemotron-3 2023 Enterprise applications[4]
Nemotron-4 2024 Synthetic-data generation[5]
Llama Nemotron 2025 Llama-based reasoning[6]
Nemotron 3 2025 Agentic AI[2]
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The Nemotron 3 models use a hybrid architecture combining Mamba, Transformer, and mixture of experts components.[3]

More information Model, Parameters ...
Nemotron 3 models
Model Parameters Intended use
Nano 30B; 3B active Efficient agents[2]
Super 120B; 12B active Agentic reasoning[7][9]
Ultra 550B; 55B active Complex reasoning[8]
Nano Omni 30B; 3B active Multimodal agents[10]
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Nano Omni supports text, image, video and audio input.[10] Nemotron models can be downloaded for local deployment or accessed through Nvidia's application programming interfaces and NIM inference services.[11][12]

See also

References

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