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Nemotron 3 Nano Omni, a new multimodal model, extends the Nemotron series by natively incorporating audio inputs alongside text, images, and video. It achieves accuracy improvements over Nemotron Nano V2 VL across modalities through architectural enhancements, refined training data, and optimized training recipes. Key results include state-of-the-art performance in document understanding, long audio-video comprehension, and agentic computer use, while also achieving lower inference latency via multimodal token-reduction techniques.
Multimodal models can now handle audio natively with improved efficiency, achieving state-of-the-art results in complex tasks like document understanding and agentic computer use.
We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 Nano Omni delivers consistent accuracy improvements over its predecessor, Nemotron Nano V2 VL, across all modalities, enabled by advances in architecture, training data and recipes. In particular, Nemotron 3 delivers leading results in real-world document understanding, long audio-video comprehension, and agentic computer use. Built on the highly efficient Nemotron 3 Nano 30B-A3B backbone, Nemotron 3 Nano Omni further incorporates innovative multimodal token-reduction techniques to deliver substantially lower inference latency and higher throughput than other models of similar size. We are releasing model checkpoints in BF16, FP8, and FP4 formats, along with portions of the training data and codebase to facilitate further research and development.
Amazon Science
NVIDIA