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NVIDIA today announced the NVIDIA Nemotron™ 3 family of open models, data and libraries designed to power transparent, efficient and specialized agentic AI development across industries.
The Nemotron 3 models — with Nano, Super and Ultra sizes — introduce a breakthrough hybrid latent mixture-of-experts (MoE) architecture that helps developers build and deploy reliable multi-agent systems at scale.
As organizations shift from single-model chatbots to collaborative multi-agent AI systems, developers face mounting challenges, including communication overhead, context drift and high inference costs. In addition, developers require transparency to trust the models that will automate their complex workflows. Nemotron 3 directly addresses these challenges, delivering the performance and openness customers need to build specialized, agentic AI.
“Open innovation is the foundation of AI progress,” said Jensen Huang, founder and CEO of NVIDIA. “With Nemotron, we’re transforming advanced AI into an open platform that gives developers the transparency and efficiency they need to build agentic systems at scale.”
NVIDIA Nemotron supports NVIDIA’s broader sovereign AI efforts, with organizations from Europe to South Korea adopting open, transparent and efficient models that allow them to build AI systems aligned to their own data, regulations and values.
Early adopters, including Accenture, Cadence, CrowdStrike, Cursor, Deloitte, EY, Oracle Cloud Infrastructure, Palantir, Perplexity, ServiceNow, Siemens, Synopsys and Zoom, are integrating models from the Nemotron family to power AI workflows across manufacturing, cybersecurity, software development, media, communications and other industries.
“NVIDIA and ServiceNow have been shaping the future of AI for years, and the best is yet to come,” Bill McDermott, chairman and CEO of ServiceNow. “Today, we’re taking a major step forward in empowering leaders across all industries to fast-track their agentic AI strategy. ServiceNow’s intelligent workflow automation combined with NVIDIA Nemotron 3 will continue to define the standard with unmatched efficiency, speed and accuracy.”
As multi-agent AI systems expand, developers are increasingly relying on proprietary models for state-of-the-art reasoning while using more efficient and customizable open models to drive down costs. Routing tasks between frontier-level models and Nemotron in a single workflow gives agents the most intelligence while optimizing tokenomics.
"Perplexity is built on the idea that human curiosity will be amplified by accurate AI built into exceptional tools, like AI assistants," said Aravind Srinivas, CEO of Perplexity. “With our agent router, we can direct workloads to the best fine-tuned open models, like Nemotron 3 Ultra, or leverage leading proprietary models when tasks benefit from their unique capabilities — ensuring our AI assistants operate with exceptional speed, efficiency and scale.”
The open Nemotron 3 models enable startups to build and iterate faster on AI agents and accelerate innovation from prototype to enterprise deployment. General Catalyst, Mayfield and Sierra Ventures’ portfolio companies are exploring Nemotron 3 to build AI teammates that support human-AI collaboration.
“NVIDIA’s open model stack and the NVIDIA Inception program give early-stage companies the models, tools and a cost-effective infrastructure to experiment, differentiate and scale fast,” said Navin Chaddha, managing partner at Mayfield. “Nemotron 3 gives founders a running start on building agentic AI applications and AI teammates, and helps them tap into NVIDIA’s massive installed base.”
Nemotron 3 Reinvents Multi-Agent AI With Efficiency and Accuracy
The Nemotron 3 family of MoE models includes three sizes:
Nemotron 3 Nano, a small, 30-billion-parameter model that activates up to 3 billion parameters at a time for targeted, highly efficient tasks.
Nemotron 3 Super, a high-accuracy reasoning model with approximately 100 billion parameters and up to 10 billion active per token, for multi-agent applications.
Nemotron 3 Ultra, a large reasoning engine with about 500 billion parameters and up to 50 billion active per token, for complex AI applications.
Available today, Nemotron 3 Nano is the most compute-cost-efficient model, optimized for tasks such as software debugging, content summarization, AI assistant workflows and information retrieval at low inference costs. The model uses a unique hybrid MoE architecture to deliver gains in efficiency and scalability.
This design achieves up to 4x higher token throughput compared with Nemotron 2 Nano and reduces reasoning-token generation by up to 60%, significantly lowering inference costs. With a 1-million-token context window, Nemotron 3 Nano remembers more, making it more accurate and better capable of connecting information over long, multistep tasks.
Artificial Analysis, an independent organization that benchmarks AI, ranked the model as the most open and efficient among models of the same size, with leading accuracy.
Nemotron 3 Super excels at applications that require many collaborating agents to achieve complex tasks with low latency. Nemotron 3 Ultra serves as an advanced reasoning engine for AI workflows that demand deep research and strategic planning.
Nemotron 3 Super and Ultra use NVIDIA’s ultraefficient 4-bit NVFP4 training format on the NVIDIA Blackwell architecture, significantly cutting memory requirements and speeding up training. This efficiency allows larger models to be trained on existing infrastructure without compromising accuracy relative to higher-precision formats.
With the Nemotron 3 family of models, developers can choose the open model that is right-sized for their specific workloads, scaling from dozens to hundreds of agents while benefiting from faster, more accurate long-horizon reasoning for complex workflows.
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