This approach increases latency through repeated inference passes, fragments context across modalities, and adds cost and inaccuracies over time.

By combining vision and audio encoders within its 30B-A3B, hybrid mixture-of-experts architecture, Nemotron 3 Nano Omni eliminates the need for separate perception models, driving inference efficiency at scale. It pairs this efficiency with strong multimodal perception accuracy, enabling AI systems to achieve 9x higher throughput than other open omni models with the same interactivity. The result is lower costs and better scalability without sacrificing responsiveness or quality.

In agentic systems, Nemotron 3 Nano Omni can work alongside proprietary cloud models or other NVIDIA Nemotron open models — such as Nemotron 3 Super for high-frequency execution or Nemotron 3 Ultra for complex planning — as well as proprietary models from other providers, to power sub-agents for agentic workflows such as computer use, document intelligence and audio-video reasoning.