--- title: "Efficiency Boosted 9 Times! NVIDIA's New Model Nemotron 3 Nano Omni Targets AI Agent Implementation, Integrating Speech, Vision, and Reasoning Capabilities" type: "News" locale: "en" url: "https://longbridge.com/en/news/284441916.md" description: "Despite expanding capabilities into multimodal and AI agent scenarios, the new model maintains the Nano positioning, emphasizing high cost-performance ratio and inference efficiency. With 30 billion parameters and 3 billion activated parameters, it supports ultra-long contexts of up to one million tokens. Companies in the AI and software sectors, such as Foxconn and Palantir, have already adopted the new model, while Dell and Oracle are currently evaluating it" datetime: "2026-04-28T16:04:44.000Z" locales: - [zh-CN](https://longbridge.com/zh-CN/news/284441916.md) - [en](https://longbridge.com/en/news/284441916.md) - [zh-HK](https://longbridge.com/zh-HK/news/284441916.md) --- # Efficiency Boosted 9 Times! NVIDIA's New Model Nemotron 3 Nano Omni Targets AI Agent Implementation, Integrating Speech, Vision, and Reasoning Capabilities As the competition in artificial intelligence (AI) agents intensifies, NVIDIA is accelerating its expansion from a "computing power hegemon" to a "model platform provider." On Tuesday, the 28th (US Eastern Time), NVIDIA announced on its company blog the launch of a new open-source model named Nemotron 3 Nano Omni. Featuring "native omnimodal understanding + efficient inference," the model aims to provide an integrated foundation for enterprise-level AI agents. NVIDIA stated that this industry-leading open-source omnimodal reasoning model integrates vision, audio, and language capabilities, helping AI agents achieve up to a 9x improvement in efficiency. NVIDIA introduced that a batch of companies in the AI and software sectors have been among the first to adopt Nemotron 3 Nano Omni, including Aible, Applied Scientific Intelligence (ASI), Eka Care, Foxconn, H Company, Palantir, and Pyler. In addition, Dell, DocuSign, Infosys, K-Dense, Lila, Oracle, and Zefr are currently evaluating the model. ## **Focus on Omni: One Model Bridging Speech, Vision, and Language** Unlike traditional multimodal models that typically achieve capability fusion by stitching together multiple sub-models, Nemotron 3 Nano Omni emphasizes "native omnimodal understanding." It can simultaneously process text, image, audio, and even video inputs, completing understanding and reasoning tasks within a unified architecture. In its technical blog, NVIDIA pointed out that the model has the ability to extract information from videos and documents, supporting cross-modal reasoning in complex scenarios. For example, it can enhance video understanding through speech transcription or combine OCR to parse visual text content. From an architectural perspective, Nemotron 3 Nano Omni continues the hybrid architecture route of the Nemotron 3 series: it fuses Transformer and Mamba mechanisms and introduces Mixture of Experts (MoE) to significantly reduce inference costs while maintaining performance. ## **Targeting AI Agents: Moving from Understanding to Execution** The core keyword of this release is not multimodality, but agents. NVIDIA explicitly positions the Nemotron 3 series as the foundation model for agentic AI, meaning it is used not only for content generation but also for driving agent systems with decision-making and execution capabilities. Official materials indicate that Nano Omni is the first "production-grade open model," designed specifically for building scalable AI agents. It supports capabilities such as long context, multi-step reasoning, and tool invocation. At the same time, the model introduces GUI training data, enabling AI to understand and operate interface elements. This brings it closer to real-world application scenarios, such as automating office workflows, software operations, and even executing complex workflows. Media interpretations suggest that this "omnimodal + Agent" combination means AI systems can directly process unstructured data from the real world (videos, speech, documents) and make decisions based on it, thereby expanding the boundaries of AI deployment in enterprises. ## **Efficiency Remains the Core Selling Point: Small Models Leveraging Large Capabilities** Despite expanding capabilities into multimodal and AI agent scenarios, Nemotron 3 Nano Omni maintains the "Nano" positioning, emphasizing high cost-performance ratio and inference efficiency. The Nemotron 3 Nano base model adopts a scale of approximately 30 billion parameters, but through the MoE mechanism, only 3 billion parameters are activated at a time, achieving a balance between performance and cost. Meanwhile, the series of models supports ultra-long contexts (up to the million-token level), making it suitable for processing complex documents and long-process tasks. Within NVIDIA's overall product system, Nano, Super, and Ultra form a gradient: Nano emphasizes efficiency, Super targets high-throughput enterprise scenarios, and Ultra aims at cutting-edge reasoning capabilities. ## **Open-Source Ecosystem Competing Against Closed-Source Camps** Notably, NVIDIA once again emphasizes "openness." Nemotron 3 Nano Omni not only opens up model weights but also provides supporting training data, toolchains (such as NeMo), and optimization solutions, attempting to create a complete development ecosystem. This strategy comes at a time when differentiation in the AI industry is intensifying: on one hand, some leading vendors are gradually shifting towards closed sources; on the other hand, China and the open-source community are continuously promoting open models. NVIDIA attempts to enter the middle ground with "openness + high performance" to attract developers and enterprise customers. From a broader macro perspective, as AI applications move from "chatbots" to "intelligent agents," the competition in model capabilities is upgrading from single-language understanding to a systemic competition involving multimodal fusion and task execution capabilities. The launch of Nemotron 3 Nano Omni marks that NVIDIA intends not only to sell "shovels" (GPUs) but also to provide "construction plans" (models and toolchains), further deepening its vertical layout in the AI industry chain. ### Related Stocks - [NVDA.US](https://longbridge.com/en/quote/NVDA.US.md) - [NVDL.US](https://longbridge.com/en/quote/NVDL.US.md) - [NVDU.US](https://longbridge.com/en/quote/NVDU.US.md) - [NVDX.US](https://longbridge.com/en/quote/NVDX.US.md) - [07788.HK](https://longbridge.com/en/quote/07788.HK.md) - [07388.HK](https://longbridge.com/en/quote/07388.HK.md) - [NVDY.US](https://longbridge.com/en/quote/NVDY.US.md) - [NVDD.US](https://longbridge.com/en/quote/NVDD.US.md) - [NVDQ.US](https://longbridge.com/en/quote/NVDQ.US.md) - [SOXL.US](https://longbridge.com/en/quote/SOXL.US.md) ## Related News & Research - [April 2026: NVIDIA unveils Nemotron 3 Nano Omni with 9x AI efficiency boost combining vision, audio, and language.](https://longbridge.com/en/news/284498825.md) - [Cognex Launches In-Sight Vision Controller Powered by NVIDIA | CGNX Stock News](https://longbridge.com/en/news/284392600.md) - [Nvidia stock just hit a new all-time high, pushing its market cap above $5 trillion. 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