SAN JOSE, Calif. – In a two-hour mega-event NVIDIA Corp. CEO Jensen Huang dubbed the “Super Bowl of AI,” NVIDIA Corp. kicked off its annual GTC conference on Monday with a sweeping refresh of its hardware and software ecosystem.
The center of the storm is the new Vera Rubin platform, a massive infrastructure project designed to transition the industry from simple generative models to agentic artificial intelligence (AI).
The Vera Rubin platform, a unified supercomputing architecture, integrates seven new chips in full production, including Vera CPU and Rubin GPU. Combined with high-speed networking components like the NVLink 6 Switch and the newly integrated Groq 3 LPU, the platform is engineered to function as a singular, massive AI factory.
“Vera Rubin is a generational leap,” Huang said during a keynote speech at the cavernous SAP Center here. “The agentic AI inflection point has arrived, kicking off the greatest infrastructure buildout in history.”
NVIDIA projects more than $1 trillion in potential Blackwell/Rubin revenue through 2027, twice the $500 billion it estimated in October, according to Wedbush Securities.
“We are now a computing platform that runs all of AI,” said Huang, who also acknowledged the importance of apps during his speech.
Vera CPU stood out as the crown jewel at the digital three-ring circus. As the world’s first processor purpose-built for reinforcement learning and agentic workflows, it delivers twice the efficiency of traditional rack-scale CPUs. Its high single-thread performance is specifically tuned for the reasoning phase of AI, where models must validate code, interact with data, and manage tools, according to NVIDIA.
Industry giants lined up in support. Hyperscalers Meta Platforms Inc., Alibaba, and Oracle Cloud, alongside hardware leaders Dell Inc. and Lenovo Group have committed to deploying Vera architecture. The broad support positions NVIDIA to standardize the infrastructure used by everyone from startups to global enterprises.
“This announcement clearly signals that the largest enterprises are adopting agents,” Alex Laurie, chief technology officer at Ping Identity, said in an email.
“NVIDIA is making a big claim at GTC 2026: agentic AI doesn’t just have a model problem, it has an infrastructure problem, and NVIDIA intends to be the one to solve it,” said Mitch Ashley, vice president and practice lead, Software Lifecycle Engineering, at The Futurum Group. “That’s my read of their emerging ‘agent stack,’ not their official language.”
Jack Gold, a long-time tech analyst, observed NVIDIA is “trying hard to reposition itself as the inference AI company, after it spent so much time being the premier training company over the past few years, and especially now that there are so many newcomers pushing into inference.”
“We estimate 80% to 85% or AI workloads will be inference in the next one to two 2 years, so NVIDIA must be a major player there,” Gold said. “A complimentary issue to this is that Inference won’t spend the gigabucks that is being spent on training, so NVIDIA is pushing the message that Vera Rubin and its AI factories are lowering the overall cost of tokens, even as the cost of these systems goes up. Inference is a cost sensitive compute structure, just like cloud hosting is.”
Beyond the digital realm, NVIDIA is pushing deep into physical AI. The company unveiled Physical AI Data Factory Blueprint, an open architecture aimed at automating how robotics data is generated and evaluated. In partnering with robotics pioneers Boston Dynamics (via Agility), ABB, and KUKA, NVIDIA is providing the brains for the next generation of humanoid robots and industrial automation through its Isaac and Cosmos simulation frameworks.
NVIDIA’s ambitions also extended beyond Earth’s atmosphere. The company introduced the Vera Rubin Space Module, bringing data-center-class compute to orbital data centers. The Rubin GPU offers up to 25 times more AI compute for space-based inferencing than the previous H100 model, allowing for autonomous space operations and advanced geospatial intelligence in power-constrained environments.
A parade of announcements with third parties were also shared, a testament to NVIDIA’s stature as AI’s central hub.
Adobe Inc. and NVIDIA forged a strategic partnership to overhaul the digital content pipeline, integrating NVIDIA’s accelerated computing and open-source models directly into Adobe’s creative and marketing suites. The collaboration aims to supercharge the development of next-generation Adobe Firefly foundational models and introduce agentic workflows, which use AI to automate complex production tasks.
The alliance merges Adobe’s industry-standard creative tools with NVIDIA’s research and library infrastructure to address skyrocketing demand for personalized digital assets.
AI cloud provider Nebius entered a strategic collaboration with NVIDIA to launch an end-to-end platform specifically engineered for physical AI. Unlike traditional cloud workloads, physical AI requires a seamless loop between virtual simulation and real-world hardware.
The new platform is designed to support the entire robotics lifecycle, from creating high-fidelity digital twins and leveraging massive compute for neural network development to scaling fleet operations in the real world.
“Physical AI is going to be one of the defining technology shifts of this decade,” said Evan Helda, head of physical AI at Nebius. He noted that current development teams are often limited by legacy infrastructure. “Working with NVIDIA, we are building the execution layer for the entire physical AI ecosystem,” he said.
Simultaneously, Lenovo unveiled the next phase of its Hybrid AI Advantage with NVIDIA. The suite of solutions is focused on performance metrics that matter to the bottom line — specifically reducing Time-to-First-Token and accelerating the deployment of generative AI across diverse environments.
The expansion marks a significant scale-up from Lenovo’s previous inferencing tools, now spanning personal devices for AI-enhanced edge computing, enterprise data centers for on-premise private clouds, and gigawatt-scale cloud for massive deployments for global industrial automation.
By integrating NVIDIA’s acceleration libraries, Lenovo aims to enable real-time decision-making and intelligent automation at a global scale, moving AI from a pilot project phase into a core operational driver for heavy industry and global enterprises.
GMI Cloud, a full-stack AI infrastructure provider, launched a global initiative to architect and deploy sovereign AI factories. The company is positioning itself as a primary backbone for these national-scale projects by integrating a significant capacity of the newly announced NVIDIA Vera Rubin NVL72 platform. By bringing this high-performance hardware online, GMI Cloud intends to establish a new gold standard for government-led AI deployments.
The initiative is already underway, marking a strategic shift toward AI sovereignty as countries seek to maintain control over their data and domestic technological capabilities.
