NVIDIA Nemotron

Nemotron 3 Nano 30B A3B

• Nemotron 3 Nano offers 4x faster throughput compared to Nemotron 2 Nano
• Leading accuracy for coding, reasoning, math and long context tasks
• Perfect for agents that need to deliver highest accuracy and efficiency for targeted tasks

Nemotron 3 Nano Omni 30B A3B

• Single model for video, audio, image, and text understanding for a simplified agent workflow
• Multimodal reasoning for sub-agents within agentic use cases such as computer use agent, document intelligence, and video/audio understanding
• Highest in-class efficiency and with low costs

Nemotron 3 Super 120B A12B

• Highest in-class efficiency and leading accuracy
• Great for addressing complex tasks in multi-agent environment
• Suitable for single data center GPU deployments

Llama Nemotron Ultra 253B

• Ideal for multi-agent enterprise workflows requiring highest accuracy, such as customer service automation, supply chain management, and IT security
• Suitable for data center-scale deployments

Nemotron Parse

• Understands document semantics and extract text and tables elements with spatial grounding
• Overcomes traditional OCR limitations with support for multi-column layouts, LaTeX table extraction, markdown formatting, and reading-order reconstruction
• Designed to accelerate document intelligence pipelines for RAG, LLM training data curation, and agentic document workflows
  

Nemotron RAG

• Industry-leading extraction, embed, and rerank models
• Best-in-class accuracy for multimodal document intelligence, question answering, and passage retrieval
  
• Leading positions on ViDoRe V1, ViDoRe V2, and MTEB  and MMTEB leaderboard

Nemotron Speech

• A family of open models optimized for high-throughput, ultra-low latency automatic speech recognition (ASR), text-to-speech (TTS), speech-to-speech (S2S), full-duplex, and neural machine translation (NMT) for agentic AI applications
• Nemotron Speech models with the NVIDIA Riva GPU-accelerated speech AI library deliver state-of-the-art ASR and TTS capabilities for seamless production deployment

Nemotron Safety

• Advanced multilingual, multimodal safety models that deliver high accuracy jailbreak detection, content moderation with cultural nuance, fine-grained PII detection, reasoning-based custom policy enforcement, and topic control for more secure and more compliant LLMs across global domains and use cases.
• NeMo Guardrails,  a flexible, open library for defining and enforcing enterprise AI policies in real time—covering dialogue control, topic guidance, RAG grounding, tool‑call governance, safety filtering, and more—with parallel, low‑latency execution across custom, community, and NVIDIA safety rails.

Nemotron Pre- and Post-Training Datasets

NVIDIA provides over 10T tokens of multilingual reasoning, coding, and safety data to help the community build their custom models.

Nemotron Personas Datasets

Fully synthetic, privacy-safe personas are grounded in real-world demographic, geographic, and cultural distributions. Part of NVIDIA’s growing global collection for Sovereign AI development, featuring datasets for USA, Japan, India, Singapore, Brazil, France, and South Korea.

Nemotron Omni Datasets

Multimodal data extending the Nemotron training pipeline beyond text to image, video, and speech. ~127B tokens of cross-modal pretraining data and ~124M curated post-training examples for document reasoning, computer use, and long-horizon workflows.

Nemotron Safety Datasets

High-quality, curated datasets built to power multilingual content safety, advanced policy reasoning, and threat-aware AI—spanning moderation data and audio-based safety signals for modern AI assistants.

Nemotron RL Datasets

Train models with the same reinforcement learning (RL) data powering Nemotron, including multi-turn trajectories, tool calls, and preference signals across coding, math, reasoning, and agentic tasks to build adaptive, reliable real-world AI.

Nemotron RAG Datasets

Unlock the foundation behind our leaderboard-topping model with the release of 15 meticulously curated datasets—spanning instruction-following, reasoning, coding, and evaluation data—to accelerate open research and transparent model development.

NVIDIA NeMo

Simplify AI agent lifecycle management by fine-tuning, deploying, and continuously optimizing Nemotron models with NVIDIA NeMo™.

NVIDIA TensorRT-LLM

TensorRT™-LLM is an open-source library built to deliver high-performance, real-time inference optimization for large language models like Nemotron on NVIDIA GPUs. This open-source library is available on the TensorRT-LLM GitHub repo and includes a modular Python runtime, PyTorch-native model authoring, and a stable production API.

Open-Source Frameworks

Deploy Nemotron models using open-source frameworks such as Hugging Face transformers for development or vLLM for deployment and production use cases on all supported platforms.

Power Specialized AI Agents For Targeted Tasks With Efficient NVIDIA Nemotron 3 Nano Accuracy

NVIDIA Nemotron 3 Nano brings advanced reasoning and agentic capabilities with high efficiency using hybrid Transformer-Mamba MoE architecture and a configurable thinking budget—so you can dial accuracy, throughput, and cost to match your real‑world needs.

How to Build a Voice-Powered RAG Agent Using New Nemotron Models

Get a step-by-step guide on how to build a voice-powered RAG agent by integrating Nemotron models for speech, RAG, safety, and long-context reasoning.

Nemotron 3 Super: Open Hybrid Mamba-Transformer MoE for Agentic Reasoning

Nemotron 3 Super, a hybrid Mamba‑Transformer MoE model for large‑scale agentic AI, combines latent MoE, multi‑token prediction, and a 1M‑token context window for faster, more reliable long‑horizon reasoning. Native NVFP4 training, multi‑environment RL alignment, and fully open weights, datasets, recipes, and deployment cookbooks help developers quickly build and deploy customized agentic workflows.