Nvidia Unleashes Nemotron 3: Advancing Open Agentic AI
December 19, 2025, 9:38 pm
Location: Australia, New South Wales, Concord
Employees: 51-200
Founded date: 2016
Total raised: $494M
Nvidia unveils Nemotron 3, a groundbreaking open AI model family. These models — Nano, Super, Ultra — drive the next generation of sophisticated agentic AI systems across sectors. They harness a hybrid Mixture-of-Experts architecture for unparalleled efficiency, intelligence, and scalability. Nemotron 3 boasts a four-fold throughput increase, drastically reduced operational costs, and an expansive one-million-token context window. Nvidia supplements this with robust new training datasets and critical safety tools. This release underscores Nvidia's unwavering commitment to open innovation and empowering developers. It propels the industry toward complex, orchestrated AI applications, fundamentally reshaping enterprise AI development and deployment.
Nvidia has announced Nemotron 3. This new model family targets advanced agentic artificial intelligence. It represents a significant step in AI development. The industry shifts towards more complex, orchestrated AI applications. Nemotron 3 provides the foundation.
Nemotron 3 arrives in three distinct sizes. Each model serves specific AI operational needs. These include Nano, Super, and Ultra.
Nemotron 3 Nano is the smallest. It features 30 billion parameters, with 3 billion active. This model focuses on targeted, highly efficient tasks. Nano delivers four times the throughput of its predecessor. High performance remains a priority. Nano is available immediately.
Nemotron 3 Super scales up. It combines 100 billion parameters with 10 billion active. Super provides mid-range intelligence. It excels in multi-agent applications. These scenarios involve collaborative tasks. Low latency is crucial. Super will launch in early 2026.
Nemotron 3 Ultra stands as the largest. This powerful engine boasts 500 billion parameters, with 50 billion active. Ultra handles complex AI applications. It facilitates demanding AI workflows. Deep research and long-horizon strategic planning become possible. Ultra is expected in mid-2026.
Nvidia built Nemotron 3 on a breakthrough architecture. It uses a hybrid latent Mixture-of-Experts (MoE) method. This design compresses memory needs. It optimizes compute resources. It delivers exceptional intelligence for its size.
The MoE architecture enhances scalability. It boosts overall efficiency. Generation costs see a significant reduction. This can reach up to 60%. The architecture improves token throughput. It offers up to a four-fold increase.
Nemotron 3 models benefit from advanced training. They utilize the ultra-efficient 4-bit NVPF4 format. This allows deployment on Nvidia’s Blackwell architecture. Fewer graphics processing units are required. The memory footprint shrinks. This efficient process enables distillation. Accuracy and reasoning capabilities remain high.
A key feature is the expanded context window. Nemotron 3 supports one million tokens. This allows models to process vast amounts of information. Complex problem-solving becomes more robust.
The AI landscape evolves rapidly. Single-model chatbots are becoming obsolete. The future belongs to orchestrated AI applications. These systems automate multiple models. They power proactive, intelligent agents. Nemotron 3 directly addresses this shift.
Agentic AI demands advanced reasoning. It requires sophisticated tool orchestration. Nvidia’s new models meet these challenges head-on. They position Nvidia strategically. The competition moves beyond raw parameter counts. Focus shifts to orchestration, reliability, and agent-centric performance.
Nemotron 3 helps drive down operational costs. It maintains high-speed, reliable reasoning. This makes advanced AI accessible. It enables broader industry adoption.
Nvidia champions open innovation. Nemotron 3 exemplifies this commitment. It provides developers transparency and efficiency. They can build agentic systems at scale.
The company actively fosters an ecosystem-driven approach. Developers gain freedom in model customization. They can create specialized AI. The models are highly optimized for Nvidia platforms. This includes graphics cards. However, they do not strictly require Nvidia hardware.
Nvidia also aims for reliability. It promises a clear roadmap for model releases. Developers need predictable expectations. This includes model maturity and long-term support. Open-source families offer greater stability.
Nemotron 3 is not just about models. Nvidia also releases critical supporting resources. These enable specialized AI agent development.
A collection of training datasets is available. This includes 3 trillion tokens. These cover pre-training, post-training, and reinforcement learning. They provide rich examples. These span reasoning, coding, and multistep workflows. This framework supports highly capable, domain-specialized agents.
Reinforcement learning is vital. It trains AI models through real-world scenarios. Models learn by doing. Successful actions receive rewards. Mistakes incur penalties. This creates reasoning systems. They operate in complex, dynamic conditions. They learn rules through active feedback.
Nvidia introduces the Nemotron Agentic Safety Dataset. This real-world telemetry dataset is crucial. It helps teams evaluate and strengthen safety. This applies to complex and multi-agent systems.
Furthermore, Nvidia released NeMo Gym and NeMo RL. These are open-source libraries. NeMo Gym provides training environments. NeMo RL offers a post-training foundation. Developers use them together. They accelerate development. Models run through test environments. RL training loops integrate seamlessly.
These transparent datasets and tools solve an industry challenge. Developers often struggle to trust models in production. Nvidia helps define operational boundaries. Teams can train models for specific tasks. They can rigorously evaluate reliability before deployment.
Early adopters are already leveraging Nemotron 3. These include Accenture, CrowdStrike, Oracle Cloud Infrastructure, Palantir, Perplexity AI, ServiceNow, Siemens, and Zoom. Other early users include Cursor, Deloitte, and EY. This broad adoption showcases industry trust. It validates Nemotron 3’s potential.
Nvidia’s Nemotron 3 launch marks a pivotal moment. It propels the evolution of AI. It empowers developers with powerful open models. It provides the essential tools for building the next generation of intelligent agents. The future of AI is agentic. Nvidia is paving the way. This fosters innovation. It drives technological progress across global industries.
Nvidia has announced Nemotron 3. This new model family targets advanced agentic artificial intelligence. It represents a significant step in AI development. The industry shifts towards more complex, orchestrated AI applications. Nemotron 3 provides the foundation.
The Nemotron 3 Family: Powering Diverse AI Agents
Nemotron 3 arrives in three distinct sizes. Each model serves specific AI operational needs. These include Nano, Super, and Ultra.
Nemotron 3 Nano is the smallest. It features 30 billion parameters, with 3 billion active. This model focuses on targeted, highly efficient tasks. Nano delivers four times the throughput of its predecessor. High performance remains a priority. Nano is available immediately.
Nemotron 3 Super scales up. It combines 100 billion parameters with 10 billion active. Super provides mid-range intelligence. It excels in multi-agent applications. These scenarios involve collaborative tasks. Low latency is crucial. Super will launch in early 2026.
Nemotron 3 Ultra stands as the largest. This powerful engine boasts 500 billion parameters, with 50 billion active. Ultra handles complex AI applications. It facilitates demanding AI workflows. Deep research and long-horizon strategic planning become possible. Ultra is expected in mid-2026.
Architectural Breakthroughs: Efficiency and Scale
Nvidia built Nemotron 3 on a breakthrough architecture. It uses a hybrid latent Mixture-of-Experts (MoE) method. This design compresses memory needs. It optimizes compute resources. It delivers exceptional intelligence for its size.
The MoE architecture enhances scalability. It boosts overall efficiency. Generation costs see a significant reduction. This can reach up to 60%. The architecture improves token throughput. It offers up to a four-fold increase.
Nemotron 3 models benefit from advanced training. They utilize the ultra-efficient 4-bit NVPF4 format. This allows deployment on Nvidia’s Blackwell architecture. Fewer graphics processing units are required. The memory footprint shrinks. This efficient process enables distillation. Accuracy and reasoning capabilities remain high.
A key feature is the expanded context window. Nemotron 3 supports one million tokens. This allows models to process vast amounts of information. Complex problem-solving becomes more robust.
Driving the Agentic AI Revolution
The AI landscape evolves rapidly. Single-model chatbots are becoming obsolete. The future belongs to orchestrated AI applications. These systems automate multiple models. They power proactive, intelligent agents. Nemotron 3 directly addresses this shift.
Agentic AI demands advanced reasoning. It requires sophisticated tool orchestration. Nvidia’s new models meet these challenges head-on. They position Nvidia strategically. The competition moves beyond raw parameter counts. Focus shifts to orchestration, reliability, and agent-centric performance.
Nemotron 3 helps drive down operational costs. It maintains high-speed, reliable reasoning. This makes advanced AI accessible. It enables broader industry adoption.
Open Innovation and Ecosystem Empowerment
Nvidia champions open innovation. Nemotron 3 exemplifies this commitment. It provides developers transparency and efficiency. They can build agentic systems at scale.
The company actively fosters an ecosystem-driven approach. Developers gain freedom in model customization. They can create specialized AI. The models are highly optimized for Nvidia platforms. This includes graphics cards. However, they do not strictly require Nvidia hardware.
Nvidia also aims for reliability. It promises a clear roadmap for model releases. Developers need predictable expectations. This includes model maturity and long-term support. Open-source families offer greater stability.
Empowering Developers with Comprehensive Tools and Data
Nemotron 3 is not just about models. Nvidia also releases critical supporting resources. These enable specialized AI agent development.
A collection of training datasets is available. This includes 3 trillion tokens. These cover pre-training, post-training, and reinforcement learning. They provide rich examples. These span reasoning, coding, and multistep workflows. This framework supports highly capable, domain-specialized agents.
Reinforcement learning is vital. It trains AI models through real-world scenarios. Models learn by doing. Successful actions receive rewards. Mistakes incur penalties. This creates reasoning systems. They operate in complex, dynamic conditions. They learn rules through active feedback.
Nvidia introduces the Nemotron Agentic Safety Dataset. This real-world telemetry dataset is crucial. It helps teams evaluate and strengthen safety. This applies to complex and multi-agent systems.
Furthermore, Nvidia released NeMo Gym and NeMo RL. These are open-source libraries. NeMo Gym provides training environments. NeMo RL offers a post-training foundation. Developers use them together. They accelerate development. Models run through test environments. RL training loops integrate seamlessly.
These transparent datasets and tools solve an industry challenge. Developers often struggle to trust models in production. Nvidia helps define operational boundaries. Teams can train models for specific tasks. They can rigorously evaluate reliability before deployment.
Industry Adoption and Future Impact
Early adopters are already leveraging Nemotron 3. These include Accenture, CrowdStrike, Oracle Cloud Infrastructure, Palantir, Perplexity AI, ServiceNow, Siemens, and Zoom. Other early users include Cursor, Deloitte, and EY. This broad adoption showcases industry trust. It validates Nemotron 3’s potential.
Nvidia’s Nemotron 3 launch marks a pivotal moment. It propels the evolution of AI. It empowers developers with powerful open models. It provides the essential tools for building the next generation of intelligent agents. The future of AI is agentic. Nvidia is paving the way. This fosters innovation. It drives technological progress across global industries.