// Workers AI · dad joke modeWhat did the Nemotron say? "I'm attracted to data.

Nemotron
Nemotron
Developer	Nvidia
Release	November 15, 2023; 2 years ago
Type	Large language model
License	Various ; Nvidia Open Model License
Website	developer.nvidia.com/topics/ai/nemotron
Repository	github.com/NVIDIA-NeMo/Nemotron

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]

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

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]

The Nemotron 3 models use a hybrid architecture combining Mamba, Transformer, and mixture of experts components.^[3]

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]

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]

References

↑ "NVIDIA Nemotron Open Model License". Nvidia. December 15, 2025. Retrieved July 29, 2026.
1 2 3 4 Lee, Jane Lanhee (December 15, 2025). "Nvidia unveils new open-source AI models amid boom in Chinese offerings". Reuters. Retrieved July 29, 2026.
1 2 Knight, Will (December 15, 2025). "Nvidia Becomes a Major Model Maker With Nemotron 3". Wired. Retrieved July 29, 2026.
1 2 "NVIDIA AI Foundation Models: Build Custom Enterprise Chatbots and Co-Pilots With Production-Ready LLMs". Nvidia Technical Blog. Nvidia. November 15, 2023. Retrieved July 29, 2026.
1 2 Nuñez, Michael (June 14, 2024). "Nvidia's Nemotron-4 340B model redefines synthetic data generation, rivals GPT-4". VentureBeat. Retrieved July 29, 2026.
1 2 Bercovich, Akhiad; Levy, Itay; Golan, Izik; Dabbah, Mohammad; et al. (May 2, 2025). "Llama-Nemotron: Efficient Reasoning Models". arXiv:2505.00949 [cs.CL].
1 2 Knight, Will (March 11, 2026). "Nvidia Will Spend $26 Billion to Build Open-Weight AI Models, Filings Show". Wired. Retrieved July 29, 2026.
1 2 "NVIDIA Nemotron 3 Ultra". Nvidia Research. Nvidia. June 4, 2026. Retrieved July 29, 2026.
↑ "Introducing Nemotron 3 Super: An Open Hybrid Mamba-Transformer MoE for Agentic Reasoning". Nvidia Technical Blog. Nvidia. March 11, 2026. Retrieved July 31, 2026.
1 2 "NVIDIA Nemotron 3 Nano Omni Powers Multimodal Agent Reasoning in a Single Efficient Open Model". Nvidia Technical Blog. Nvidia. April 28, 2026. Retrieved July 29, 2026.
↑ Sirodot, Bertrand; Bronzati, Fabricio (November 7, 2025). "Introduction to NVIDIA Inference Microservices, aka NIM". Dell Technologies Info Hub. Dell Technologies. Retrieved July 29, 2026.
↑ "NVIDIA Nemotron". Nvidia. Nvidia. Retrieved July 29, 2026.

External links

[1] "NVIDIA Nemotron Open Model License". Nvidia. December 15, 2025. Retrieved July 29, 2026.

[Reuters2025-2] 1 2 3 4 Lee, Jane Lanhee (December 15, 2025). "Nvidia unveils new open-source AI models amid boom in Chinese offerings". Reuters. Retrieved July 29, 2026.

[Wired2025-3] 1 2 Knight, Will (December 15, 2025). "Nvidia Becomes a Major Model Maker With Nemotron 3". Wired. Retrieved July 29, 2026.

[Nvidia2023-4] 1 2 "NVIDIA AI Foundation Models: Build Custom Enterprise Chatbots and Co-Pilots With Production-Ready LLMs". Nvidia Technical Blog. Nvidia. November 15, 2023. Retrieved July 29, 2026.

[VentureBeat2024-5] 1 2 Nuñez, Michael (June 14, 2024). "Nvidia's Nemotron-4 340B model redefines synthetic data generation, rivals GPT-4". VentureBeat. Retrieved July 29, 2026.

[LlamaNemotron-6] 1 2 Bercovich, Akhiad; Levy, Itay; Golan, Izik; Dabbah, Mohammad; et al. (May 2, 2025). "Llama-Nemotron: Efficient Reasoning Models". arXiv:2505.00949 [cs.CL].

[Wired2026-7] 1 2 Knight, Will (March 11, 2026). "Nvidia Will Spend $26 Billion to Build Open-Weight AI Models, Filings Show". Wired. Retrieved July 29, 2026.

[Ultra-8] 1 2 "NVIDIA Nemotron 3 Ultra". Nvidia Research. Nvidia. June 4, 2026. Retrieved July 29, 2026.

[9] "Introducing Nemotron 3 Super: An Open Hybrid Mamba-Transformer MoE for Agentic Reasoning". Nvidia Technical Blog. Nvidia. March 11, 2026. Retrieved July 31, 2026.

[Omni-10] 1 2 "NVIDIA Nemotron 3 Nano Omni Powers Multimodal Agent Reasoning in a Single Efficient Open Model". Nvidia Technical Blog. Nvidia. April 28, 2026. Retrieved July 29, 2026.

[11] Sirodot, Bertrand; Bronzati, Fabricio (November 7, 2025). "Introduction to NVIDIA Inference Microservices, aka NIM". Dell Technologies Info Hub. Dell Technologies. Retrieved July 29, 2026.

[12] "NVIDIA Nemotron". Nvidia. Nvidia. Retrieved July 29, 2026.

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v t e Large language models (LLMs)
List of LLMs AI Companies Benchmarks List of chatbots Foundation model Generative AI
Concepts	Language model NLP NLG Computational linguistics Foundation model Small language model Reasoning model Generative pre-trained transformer Transformer Attention KV cache Context window Tokenization Word embedding Parameter Hyperparameter Autoregression Mixture of experts (MoE) Inference Model compression Knowledge distillation Speculative decoding PagedAttention Neural scaling law Multimodality Open weights
Training, prompting, and alignment	Self-supervised learning Supervised learning Fine-tuning Instruction tuning RLHF Constitutional AI AI alignment AI safety Mechanistic interpretability Prompt engineering In-context learning Chain-of-thought prompting RAG Prompt injection Adversarial machine learning Hallucination Stochastic parrot Glitch token Generative engine optimization
Models	Apertus BERT BLOOM Chinchilla Claude DBRX Gemini Gemma GloVe GLM GPT GPT-J PanGu Granite Jais LaMDA Llama MiMo Minerva Mistral and Mixtral Nemotron PaLM Phi Qwen Seq2seq T5 Vicuna Word2vec XLNet
Chatbots and assistants	Amazon Q ChatGPT Character.ai Claude DeepSeek Doubao Ernie Bot GLM Google Gemini Grok Kimi Microsoft Copilot Meta AI Perplexity AI Sparrow You.com
Agents, coding, and applications	AI agent Intelligent agent AutoGPT CrewAI LangChain Manus Model Context Protocol Agent2Agent OpenAI Codex Vibe coding Code generation Question answering Machine translation Text summarization Chatbot Virtual assistant LLMs in higher education
Software	PyTorch TensorFlow Hugging Face Inference engine llama.cpp Ollama SGLang TensorRT-LLM vLLM ONNX OpenVINO Vector database ChromaDB Deep learning software Open-source AI software
Hardware and infrastructure	AI data center AI accelerator GPU CUDA TPU High-bandwidth memory
Benchmarks, evaluation, and detection	Language model benchmark MMLU Humanity's Last Exam LMArena LLM-as-a-Judge Perplexity metric GPTZero Artificial intelligence content detection Undetectable.ai
Datasets and data	Data set Text corpus Common Crawl The Pile Web scraping Synthetic data Training, validation, and test data sets
Organizations	AI21 Labs Alibaba Anthropic Baidu Cohere DeepSeek EleutherAI Google DeepMind Hugging Face Meta AI Microsoft AI Mistral AI MiniMax Moonshot AI Nvidia OpenAI Sarvam AI StepFun Technology Innovation Institute Thinking Machines Lab xAI
People	Sam Altman Dario Amodei Yoshua Bengio Aidan Gomez Demis Hassabis Geoffrey Hinton Andrej Karpathy Yann LeCun Percy Liang Liang Wenfeng Christopher D. Manning Arthur Mensch Mira Murati Alec Radford Noam Shazeer Ilya Sutskever Ashish Vaswani Andrew Ng
Social, economic, and governance	AI boom AI bubble AI slop AI anthropomorphism AI arms race Chatbot psychosis Competition Copyright Deaths linked to chatbots Dependency (GAID) Environmental impact Regulation Ethics Existential risk In education In healthcare Workplace impact
Category:Large language models

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// Workers AI · dad joke modeWhat did the Nemotron say? "I'm attracted to data.

History

Models

See also

References

External links