NVIDIA Launches Nemotron 3 Nano Omni for 9x Efficient AI Agents
NVIDIA introduced Nemotron 3 Nano Omni on April 28, 2026. This open multimodal model integrates vision, audio, and language capabilities into a single system. It allows AI agents to provide quicker responses with better reasoning across video, audio, images, and text. The model supports production use for enterprises and developers seeking efficient multimodal AI agents with deployment options.
Nemotron 3 Nano Omni leads in efficiency among open multimodal models. It achieves top scores on six leaderboards for tasks in document intelligence, video understanding, and audio comprehension. Current AI agent systems rely on distinct models for vision, speech, and language. Data handoffs between these models cause delays and loss of context.
Model Capabilities at a Glance
Nemotron 3 Nano Omni serves as an open omni-modal reasoning model. It provides the highest efficiency and strong accuracy in its category. The model processes text, images, audio, video, documents, charts, and graphical interfaces as inputs. It generates text outputs.
Enterprises and developers use it to build fast, reliable agentic systems. It acts as the perception component, or "eyes and ears," in multi-agent setups. It pairs with models like Nemotron 3 Super for execution tasks or Nemotron 3 Ultra for planning. It also works with proprietary models from other providers.
This setup matters because it delivers leading multimodal accuracy. It achieves 9x higher throughput compared to other open omni models with matching interactivity levels. That leads to reduced costs and improved scalability while keeping responsiveness intact.
Architecture and Performance
The model uses a 30B-A3B hybrid mixture-of-experts architecture. It includes Conv3D and EVS components with a 256K context length. By merging vision and audio encoders, it removes the need for separate perception models. This boosts inference efficiency at scale.
In agentic workflows, separate models create latency from multiple inference steps. They also fragment context across modalities and raise costs with accumulating errors. Nemotron 3 Nano Omni combines these functions for up to 9x better throughput. It maintains quality and speed.
For computer use agents, it handles the perception for navigating graphical interfaces. It reasons over screen content and tracks UI states over time. H Company's computer usage agent, built on this model, processes 1920×1080 pixel inputs. Early tests on the OSWorld benchmark showed gains in handling complex interfaces and high-resolution images.
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In document intelligence, it analyzes documents, charts, tables, screenshots, and mixed media. Agents can reason across visual and text elements for enterprise analysis and compliance. For audio and video, it keeps context linked in one stream. This aids customer service, research, and monitoring by connecting speech, visuals, and documents.
Early Adoption and Feedback
Companies adopting Nemotron 3 Nano Omni include Aible, Applied Scientific Intelligence (ASI), Eka Care, Foxconn, H Company, Palantir, and Pyler. Dell Technologies, DocuSign, Infosys, K-Dense, Lila, Oracle, and Zefr are testing it.
Gautier Cloix, CEO of H Company, said, "To build useful agents, you can't wait seconds for a model to interpret a screen. By building on Nemotron 3 Nano Omni, our agents can rapidly interpret full HD screen recordings, something that wasn't practical before. This isn't just a speed boost: It's a fundamental shift in how our agents perceive and interact with digital environments in real time."
NVIDIA provides open weights, datasets, and training methods for full control. Developers can customize it with NVIDIA NeMo tools for specific domains. The open nature supports deployment in regulated or data-local environments.
The Nemotron 3 family, which includes Nano, Super, and Ultra models, recorded over 50 million downloads in the past year. Omni adds multimodal support for agentic applications.
Availability and Deployment Options
Nemotron 3 Nano Omni became available on April 28, 2026. Access it via Hugging Face, OpenRouter, build.nvidia.com, and more than 25 partner platforms. It deploys as an NVIDIA NIM microservice through cloud partners and inference services.
Its lightweight design fits local setups like NVIDIA DGX Spark and DGX Station. It also scales to data centers and clouds for consistent performance.
NVIDIA offers technical resources like tutorials and guides for use cases.