NVIDIA Debuts Nemotron 3 — Open Models With 4x Throughput and a Million-Token Context Window
NVIDIA's Nemotron 3 family ships three tiers of open models optimized for agentic AI, plus 3 trillion tokens of training data for the community.
NVIDIA just raised the bar for what open AI models can deliver to developers. The Nemotron 3 family, announced in late February, arrives in three tiers — Nano, Super, and Ultra — each designed from the ground up for the agentic AI workloads that are rapidly becoming the industry's primary focus.
Three Tiers for Different Deployment Needs
Nemotron 3 Nano targets edge devices and cost-sensitive deployments. Super occupies the middle ground for most enterprise applications. Ultra handles the most demanding reasoning and multi-step planning tasks. All three share a hybrid mixture-of-experts architecture that activates only the parameters needed for each token, dramatically reducing compute costs relative to dense models of equivalent capability.
The headlining benchmark is throughput. Nemotron 3 Nano delivers four times the tokens per second compared to its predecessor, making it practical for real-time applications where latency directly affects user experience. The entire family supports context windows up to one million tokens, enabling agentic workflows that need to process extensive documents, codebases, or conversation histories.
Open Data Changes the Equation
Perhaps more consequential than the models themselves is what NVIDIA released alongside them. The company published three trillion tokens of curated pre-training data and 18 million post-training samples. For research teams and startups that lack the resources to build massive training datasets, this is an enormous accelerant.
Open weights without open data creates models that can be used but not meaningfully improved upon. By releasing both, NVIDIA enables the community to fine-tune, distill, and adapt Nemotron 3 for specialized domains in ways that closed-weight models fundamentally cannot support.
Early Adoption Across the Industry
The adoption signals are already strong. Cursor, the AI-powered code editor, is integrating Nemotron 3 for its autocomplete and code generation features. Perplexity plans to use it within its multi-model orchestration stack. Palantir and ServiceNow are evaluating the Ultra tier for enterprise agentic deployments. These are not speculative partnerships — they represent production-grade commitments from companies with demanding performance requirements.
What This Means for the Open AI Ecosystem
NVIDIA occupies a unique position in the AI landscape. As the dominant GPU supplier, the company has a strategic interest in ensuring that powerful open models exist to drive demand for its hardware. Nemotron 3 serves that interest while simultaneously providing the developer community with tools that compete credibly with proprietary alternatives.
The combination of competitive performance, open weights, open data, and a million-token context window makes Nemotron 3 one of the most complete open model releases to date. For teams building agentic AI systems, the barriers to entry just dropped considerably.
Sources: NVIDIA Newsroom, February 2026; The New Stack, February 2026; VentureBeat, February 2026