NVIDIA CORPNVDA

NVIDIA unveiled Vera, the first CPU built for AI agents, with planned adoption by technology providers.

“• Unveiled NVIDIA Vera, the first CPU built for AI agents, with broad adoption planned across the world’s leading technology providers.”

NVIDIA introduced security innovations for Vera BlueField-4 STX delivering agentic AI storage processing.

“• Introduced new security innovations for NVIDIA Vera BlueField™-4 STX, delivering agentic AI storage processing with in-silicon security for AI factories.”

SpaceXAI will deploy NVIDIA Vera CPUs to accelerate its next generation of agentic AI applications.

“• Announced that SpaceXAI will deploy NVIDIA Vera CPUs to accelerate its next generation of agentic AI applications.”

NVIDIA Blackwell led in MLPerf Training 6.0 and AgentPerf benchmarks for agentic AI infrastructure.

“• Revealed that NVIDIA Blackwell led across every category in the MLPerf Training 6.0 benchmarks and in AgentPerf, the industry’s first agentic AI infrastructure benchmark.”

NVIDIA announced software, models, and partnerships to build autonomous AI agents for industries.

“• Announced new software, open source models and partnerships with the world’s leading software platform providers to build autonomous AI agents for industries and enterprises;”

NVIDIA launched BioNeMo Agent Toolkit for domain-specific tools in agentic life sciences.

“• Launched NVIDIA BioNeMo™ Agent Toolkit, which provides domain-specific tools and skills for the agentic life sciences era.”

NVIDIA CEO states agentic AI is generating value and scaling across companies and industries.

““The buildout of AI factories — the largest infrastructure expansion in human history — is accelerating at extraordinary speed,” said Jensen Huang, founder and CEO of NVIDIA. “Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries. NVIDIA is uniquely positioned at the center of this transformation as the only platform that runs in every cloud, powers every frontier and open source model, and scales everywhere AI is produced — from hyperscale data centers to the edge.””

NVIDIA reports on Edge Computing platform for agentic and physical AI devices.

“NVIDIA is transitioning to a new reporting framework that better reflects its current and future growth drivers. NVIDIA will have two market platforms — Data Center and Edge Computing. Within Data Center, NVIDIA will report two sub-markets, Hyperscale and ACIE, which incorporates AI Clouds, Industrial and Enterprise. Hyperscale will include revenue from the public clouds and the world’s largest consumer internet companies, while ACIE addresses NVIDIA’s growth opportunity in diverse AI purpose-built data centers and AI factories across industries and countries. Edge Computing highlights data processing devices for agentic and physical AI including PCs, game consoles, workstations, AI-RAN base stations, robotics and automotive.”

NVIDIA announced Vera Rubin platform for agentic AI and entered production with Dynamo 1.0.

“• Announced the NVIDIA Vera Rubin platform, including the NVIDIA Vera CPU, the world’s first processor purpose-built for agentic AI, and NVIDIA BlueField®-4 STX, accelerated storage infrastructure for agentic AI factories.”

NVIDIA entered production with Dynamo 1.0 software for generative and agentic inference.

“• Entered production with NVIDIA Dynamo 1.0, open source software that boosts generative and agentic inference on NVIDIA Blackwell GPUs by up to 7x, with widespread global adoption.”

NVIDIA announced NemoClaw, OpenShell, and Agent Toolkit for autonomous enterprise AI agents.

“• Announced NVIDIA NemoClaw™ for the OpenClaw agent platform, NVIDIA OpenShell™ with privacy and security controls for autonomous AI agents, and NVIDIA Agent Toolkit, an open source platform for building autonomous enterprise AI agents.”

NVIDIA expanded collaboration with Google Cloud on agentic and physical AI.

“• Expanded collaboration with Google Cloud to advance agentic and physical AI, including new NVIDIA Vera Rubin-powered A5X instances and a preview of Google Gemini models on Google Distributed Cloud running on NVIDIA Blackwell and Blackwell Ultra GPUs.”

NVIDIA CEO stated enterprise adoption of agents is skyrocketing.

““Computing demand is growing exponentially — the agentic AI inflection point has arrived. Grace Blackwell with NVLink is the king of inference today — delivering an order-of-magnitude lower cost per token — and Vera Rubin will extend that leadership even further,” said Jensen Huang, founder and CEO of NVIDIA. “Enterprise adoption of agents is skyrocketing. Our customers are racing to invest in AI compute — the factories powering the AI industrial revolution and their future growth.””

NVIDIA Blackwell Ultra delivers better performance for agentic AI.

“• Revealed that NVIDIA Blackwell Ultra delivers up to 50x better performance and 35x lower cost for agentic AI compared with the NVIDIA Hopper platform, according to new SemiAnalysis InferenceX benchmark results.”

NVIDIA debuted Nemotron 3 models and tools for agentic AI development.

“• Debuted the NVIDIA Nemotron™ 3 family of open models, data and libraries designed to power transparent, efficient and specialized agentic AI development across industries; released new open models, data and tools for agentic AI, physical AI and autonomous vehicle development.”

NVIDIA launched RTX PRO 5000 GPU to power agentic workflows.

“• Launched the NVIDIA RTX PRO™ 5000 72GB Blackwell GPU to power larger models and agentic workflows.”

NVIDIA describes GPU-powered solutions including generative AI and agentic AI systems.

“The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films. Today, it also simulates human intelligence, enabling a deeper understanding of language, science, and the physical world. Its parallel processing capabilities, supported by tens of thousands of computing cores, are essential for deep learning algorithms. This form of AI, in which software writes itself by learning from large amounts of data, can serve as the brain of computers, robots, and self-driving cars that can perceive, understand and reason about the world. GPU-powered AI solutions are being developed by thousands of enterprises to deliver services and products that would have been immensely difficult or even impossible with traditional coding. Examples include generative AI, which can create new content such as text, code, images, audio, video, molecule structures, and recommendation systems; and agentic AI where systems of AI models work in concert to automatically complete a task.”

NVIDIA details historical GPU, CUDA, and AI innovations plus software stacks for industries.

“Innovation is at our core. We have invested over $76.7 billion in research and development since our inception, yielding inventions that are essential to modern computing. Our invention of the GPU in 1999 sparked the growth of the PC gaming market and redefined computer graphics. With our introduction of CUDA in 2006, we opened the parallel processing capabilities of our GPU to a broad range of compute-intensive applications, paving the way for the emergence of modern AI. In 2012, the AlexNet neural network, trained on NVIDIA GPUs, won the ImageNet computer image recognition competition, marking the “Big Bang” moment of AI. We introduced our first Tensor Core GPU in 2017, built from the ground-up for the new era of AI, and our first autonomous driving system-on-chips, or SoC, in 2018. Our acquisition of Mellanox in 2020 expanded our offerings to include networking, enabled our platforms to be data center scale, and led to the introduction of a new processor class – the data processing unit, or DPU. Over the past 5 years, we have built full software stacks that run on top of our GPUs and CUDA to bring AI to the world’s largest industries, including NVIDIA DRIVE stack for autonomous driving, Clara for healthcare, Omniverse for physical AI applications, and NVIDIA AI Enterprise software – essentially an operating system for enterprise AI applications. In 2023, we introduced our first data center CPU, Grace, built for giant-scale AI and high-performance computing, or HPC. In 2024”

Enterprises and startups use NVIDIA platforms to build generative and agentic AI products.

“Enterprises and startups across a broad range of industries use our accelerated computing platforms to build new generative and agentic AI-enabled products and services, and/or to dramatically accelerate and reduce the costs of their workloads and workflows. The enterprise software industry uses them for new AI assistants, chatbots, and agents; the transportation industry for autonomous driving; the healthcare industry for accelerated and computer-aided drug discovery; and the financial services industry for customer support and fraud detection.”

NVIDIA expects more PC users to run generative and agentic AI locally on its GPUs.

“Gamers choose NVIDIA GPUs to enjoy immersive, increasingly cinematic virtual worlds. In addition to serving the growing number of gamers, the market for PC GPUs is expanding because of the growing population of live streamers, broadcasters, artists, and creators. With the advent of generative and agentic AI, we expect a broader set of PC users to choose NVIDIA GPUs for running these applications locally on their PC, which is critical for privacy, latency, and cost-sensitive AI applications.”

Generative and agentic AI expands market for NVIDIA workstation GPUs in enterprises.

“Professional artists, architects and designers use NVIDIA partner products accelerated with our GPUs and software platform for a range of creative, engineering, and design use cases, such as creating visual effects in movies or designing buildings and products. In addition, generative and agentic AI is expanding the market for our workstation-class GPUs, as more enterprise customers develop and deploy AI applications with their data on-premises.”

NVIDIA launched Blackwell for generative AI and unveiled Rubin platform for agentic AI.

“In fiscal year 2025, we launched the NVIDIA Blackwell architecture, a full set of data center scale infrastructure that includes GPUs, CPUs, DPUs, interconnects, switch chips and systems, and networking adapters. Blackwell excels at processing cutting edge generative AI and accelerated computing workloads with market leading performance and efficiency. Offered in a number of configurations, for customers across industries and a diverse set of AI and accelerated computing use cases. In fiscal year 2026, we unveiled the NVIDIA Rubin platform, which is expected to commence production shipments in the second half of fiscal year 2027. Built for agentic AI and reasoning, it excels at processing multi-step problem-solving and massive long-context workflows, delivering up to a 10x reduction in cost per token compared to Blackwell.”

NVIDIA Data Center revenue grew due to demand for platform used in generative and agentic AI applications.

“Data Center revenue for the second quarter was $41.1 billion, up 56% from a year ago and up 5% sequentially. The strong year-on-year and sequential growth was driven by demand for our accelerated computing platform used for large language models, recommendation engines, and generative and agentic AI applications. We continue to ramp our Blackwell architecture, which grew 17% sequentially, including our newest architecture, Blackwell Ultra. We recognized Blackwell revenue across all customer categories, led by large cloud service providers, which represented approximately 50% of Data Center revenue.”

NVIDIA Data Center revenue grew due to demand for platform used in generative and agentic AI applications.

“Data Center revenue was $41.1 billion, up 56% from a year ago and up 5% sequentially. The strong year-on-year and sequential growth was driven by demand for our accelerated computing platform used for large language models, recommendation engines, and generative and agentic AI applications. We continue to ramp our Blackwell architecture, which grew 17% sequentially, including our newest architecture, Blackwell Ultra. We recognized Blackwell revenue across”

NVIDIA revenue grew from demand for accelerated computing in large language models, generative and agentic AI applications.

“Compute & Networking revenue – The year over year increase in the second quarter and first half of fiscal year 2026 was driven by demand for our accelerated computing platform used for large language models, recommendation engines, and generative and agentic AI applications. Revenue from Data Center computing grew 62% year-on-year compared to the first half of fiscal year 2025, driven by demand for our Blackwell computing platform. Revenue from Data Center networking grew 79% year-on-year compared to the first half of fiscal year 2025 driven by the growth of NVLink compute fabric for GB200 and GB300 systems, the ramp of XDR InfiniBand products, and adoption of Ethernet for AI solutions at cloud service providers and consumer internet companies.”

NVIDIA CEO states that as AI agents become mainstream demand for AI computing will accelerate.

““Our breakthrough Blackwell NVL72 AI supercomputer — a ‘thinking machine’ designed for reasoning— is now in full-scale production across system makers and cloud service providers,” said Jensen Huang, founder and CEO of NVIDIA. “Global demand for NVIDIA’s AI infrastructure is incredibly strong. AI inference token generation has surged tenfold in just one year, and as AI agents become mainstream, the demand for AI computing will accelerate. Countries around the world are recognizing AI as essential infrastructure — just like electricity and the internet — and NVIDIA stands at the center of this profound transformation.””

NVIDIA introduced DGX SuperPOD with Blackwell Ultra GPUs for agentic AI reasoning.

“• Introduced the NVIDIA DGX SuperPOD™ built with NVIDIA Blackwell Ultra GPUs to provide AI factory supercomputing for agentic AI reasoning.”

NVIDIA announced joint initiatives with Alphabet and Google on agentic AI, robotics and drug discovery.

“• Announced joint initiatives with Alphabet and Google to advance agentic AI solutions, robotics and drug discovery.”

NVIDIA launched open Llama Nemotron models with reasoning capabilities for advanced AI agents.

“• Launched the open Llama Nemotron family of models with reasoning capabilities, providing a foundation for creating advanced AI agents.”

NVIDIA Data Center revenue grew due to demand for accelerated computing in generative and agentic AI applications.

“Data Center revenue for the first quarter was $39.1 billion, up 73% from a year ago and up 10% sequentially. The strong year-on-year and sequential growth was driven by demand for our accelerated computing platform used for large language models, recommendation engines, and generative and agentic AI applications. We saw our Blackwell architecture ramp expand to all customer categories, while large cloud service providers remained our largest at just under 50% of Data Center revenue. Data Center compute revenue was $34.2 billion, up 76% from a year ago and up 5% sequentially. Networking revenue was $5.0 billion, up 56% from a year ago and up 64% sequentially, driven by the growth of NVLink compute fabric in our GB200 systems and continued adoption of Ethernet for AI solutions at cloud service providers and consumer internet companies.”

NVIDIA data center revenue driven by demand for platform used in generative and agentic AI applications.

“Data Center revenue was $39.1 billion, up 73% from a year ago and up 10% sequentially. The strong year-on-year and sequential growth was driven by demand for our accelerated computing platform used for large language models, recommendation engines, and generative and agentic AI applications. We saw our Blackwell architecture ramp expand to all customer categories, while large cloud service providers remained our largest at just under 50% of Data Center revenue. Data Center compute revenue was $34.2 billion, up 76% from a year ago and up 5% sequentially. Networking revenue was $5.0 billion, up 56% from a year ago and up 64% sequentially, driven by the growth of NVLink compute fabric in our GB200 systems and continued adoption of Ethernet for AI solutions at cloud service providers and consumer internet companies.”

NVIDIA revenue growth driven by demand for platform used in generative and agentic AI applications.

“Compute & Networking revenue – The year over year increase in the first quarter of fiscal year 2026 was driven by demand for our accelerated computing platform used for large language models, recommendation engines, and generative and agentic AI applications. Revenue from Data Center computing grew 76% year-on-year compared to the first quarter of fiscal year 2025, driven by demand for our Blackwell computing platform. Revenue from Data Center networking grew 56% year-on-year compared to the first quarter of fiscal year 2025 driven by the growth of NVLink compute fabric in our GB200 systems and continued adoption of Ethernet for AI solutions at cloud service providers and consumer internet companies.”

NVIDIA states agentic AI and physical AI will revolutionize industries.

““We’ve successfully ramped up the massive-scale production of Blackwell AI supercomputers, achieving billions of dollars in sales in its first quarter. AI is advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries.””

NVIDIA launched AI Blueprints, Llama Nemotron models for building AI agents, and NIM microservices.

“• Launched NVIDIA AI Blueprints and Llama Nemotron model families for building AI agents and released NVIDIA NIM microservices to safeguard applications for agentic AI.”

NVIDIA unveiled NIM microservices, AI Blueprints and Llama Nemotron models for building AI agents on RTX AI PCs.

“• Unveiled NVIDIA NIM microservices, AI Blueprints and the Llama Nemotron family of open models for RTX AI PCs to help developers and enthusiasts build AI agents and creative workflows.”

NVIDIA lists risks and uncertainties around AI, agentic AI, product growth and market trends.

“Certain statements in this press release including, but not limited to, statements as to: AI advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments and related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhance”

Enterprises use NVIDIA platforms to build generative and agentic AI products and accelerate workloads.

“Enterprises and startups across a broad range of industries use our accelerated computing platforms to build new generative and agentic AI-enabled products and services, and/or to dramatically accelerate and reduce the costs of their workloads and workflows. The enterprise software industry uses them for new AI assistants, chatbots, and agents; the transportation industry for autonomous driving; the healthcare industry for accelerated and computer-aided drug discovery; and the financial services industry for customer support and fraud detection.”

NVIDIA offers DGX Cloud, AI Enterprise, NIM, NeMo and AI Blueprints to develop and deploy AI agents.

“In addition, we offer DGX Cloud, a fully managed AI-training-as-a-service platform, along with NVIDIA AI Enterprise—a comprehensive software suite designed to simplify the development and deployment of production-grade, end-to-end generative AI applications. NVIDIA AI Enterprise includes: NVIDIA NIM, which delivers a 2.5x increase in token throughput using industry-leading open and proprietary models; NVIDIA NeMo, a complete solution for curating, fine-tuning, evaluating, and safeguarding domain-adapted models; and AI Blueprints, pre-built, runnable templates that help enterprises build, optimize, and deploy AI agents while preserving privacy. These tools enable organizations to securely develop and run AI applications on NVIDIA-accelerated infrastructure anywhere.”