Nvidia Corp. announced today that it’s expanding its offerings of smarter AI models, physical intelligence for robotics and powerful enterprise AI servers.

Leading the news at the ACM SIGGRAPH 2025 computer graphics conference in Vancouver, Nvidia unveiled that the Nvidia RTX Pro 6000 Blackwell Server Edition GPU, a graphics processing unit designed for servers, is now coming to enterprise servers. This new addition will allow organizations to run large language models at high speed and these 2U form-factor rack-mountable servers will use the Blackwell architecture to deliver high-performance AI inference workloads.

“AI is reinventing computing for the first time in 60 years — what started in the cloud is now transforming the architecture of on-premises data centers,” said Jensen Huang, founder and chief executive of Nvidia.

The new Blackwell RTX Pro Servers bring GPU acceleration to traditional CPU-based workloads — including data analytics, simulation, video processing and graphics rendering — enabling up to 45 times better performance. According to Nvidia, this results in 18 times higher energy efficiency and significantly lower cost compared with CPU-only systems.

Nvidia is partnering with Cisco Systems Inc., Dell Technologies Inc., Hewlett Packard Enterprise Co., Lenovo Group Ltd. and Super Micro Computer, Inc. to offer the new servers in a variety of configurations.

“With the world’s leading server providers, we’re making Nvidia Blackwell RTX Pro Servers the standard platform for enterprise and industrial AI,” added Huang.

Smarter AI models for agentic AI

Artificial intelligence agents are forming the foundation of a growing market, as more organizations adopt their autonomous capabilities. These agents can reason through complex tasks and plan across longer time horizons.

Nvidia announced an expansion of its Nemotron model family, introducing two new models with advanced reasoning capabilities for building smarter AI agents: Nemotron Nano 2 and Llama Nemotron Super 1.5.

The company said these models deliver high accuracy for their size categories in areas such as scientific reasoning, coding, tool use, instruction following and chat. Designed to empower agents with deeper cognitive abilities, the models help AI systems explore options, weigh decisions and deliver results within defined constraints.

Nemotron Nano 2 achieves up to six times higher token generation throughput compared to other models in its class. Llama Nemotron Super 1.5 offers top-tier performance and leads in reasoning accuracy, making it suitable for handling complex enterprise tasks.

Nvidia is working with enterprise partners and consulting leaders to deploy these reasoning models. These include Zoom Video Communications Inc., which plans to integrate Nemotron into its AI Companion, as well as CrowdStrike Holdings Inc., which is testing the models in its Charlotte AI agents for writing cybersecurity queries, and Ernst & Young Global Ltd., adopting Nemotron Nano 2 to empower agents analyzing business data.

Physical AI and empowering reasoning robotics

Nvidia is empowering robotics and machines to “see” and reason about the world with new AI models that combine both the ability to ingest visual information and additionally think about that information.

Vision language models, or VLMs, provided computer vision for robotics, allowing them to understand and interact with the world, but they lacked the ability to think about their actions.

Today, Nvidia announced Cosmos Reason, a new open, customizable 7 billion-parameter reasoning VLM for physical AI vision agents and robotics. It allows robots and vision agents to think about what they see similar to humans and plan about what’s in a scene using intelligence such as physics knowledge and common sense from training data.

The company said it can help automate the curation and annotation of large, diverse training datasets, accelerating the development of high-accuracy AI models. It added that it can also serve as a sophisticated reasoning engine for robot planning, parsing complex instructions into steps for VLA models, even in new environments.

These new advances form the foundation for smart cities, facilities and industrial processes. Nvidia said it’s working with companies that include Accenture plc, Belden Inc., DeepHow Inc., Milestone Systems A/C and Telit Cinterion Ltd. to increase productivity and safety at their locations using physical AI-based perception and reasoning.

Infrastructure that can perceive, reason and react that relies on sensors and vision AI using the Nvidia Metropolis platform, which makes it possible to develop and deploy video analytics AI agents and services for campuses and facilities.

Images: Nvidia