Oracle and Nvidia plan to expand their cloud computing infrastructure to multi-gigawatt scale, targeting growing demand for artificial intelligence training, inference and autonomous AI agents, the companies announced today.
The expansion will add Nvidia’s Vera Rubin NVL72 systems to Oracle Cloud Infrastructure (OCI) supercomputers, while Nvidia Vera central processing units (CPUs) have become generally available on the platform, the companies said in a statement.
The agreement underscores efforts by cloud providers to build increasingly powerful infrastructure as companies deploy AI models that require vast amounts of computing capacity, electricity and cooling. The planned expansion also reflects a shift towards agentic AI systems, which can execute tasks using software tools and code rather than simply generating responses.
Oracle said its superclusters combine Nvidia’s graphics processing units (GPUs), networking equipment and data-centre infrastructure to train and serve large AI models. Each NVL72 rack connects 72 GPUs through Nvidia’s NVLink networking technology, while the wider network is designed to scale across hundreds of thousands of GPUs.
The planned expansion builds on Oracle’s existing infrastructure using Nvidia’s GB200 and GB300 NVL72 systems. Oracle also plans to introduce Nvidia HGX Rubin NVL8 systems, which connect eight Rubin GPUs in servers based on the x86 computing architecture.
The HGX Rubin NVL8 configuration is planned to include two 64-core Intel Xeon 6 CPUs, 4 terabytes of DDR5 memory and 6.4 terabits per second of high-speed networking, Oracle said. The system is intended to support AI training, fine-tuning and inference while remaining compatible with applications designed for x86 servers.
OpenAI has already used Oracle’s infrastructure to train and serve its AI models. The companies said OpenAI trained and served GPT-6 Astra in Abilene, Texas, on an Oracle supercluster containing more than 100,000 Nvidia Blackwell GPUs.
“As our frontier models advance, we need infrastructure that can keep pace,” said Sreekanth Pothanis, engineering leader, compute infra at OpenAI. “NVIDIA Vera Rubin on OCI gives us the computing performance and scale to accelerate model training and serve increasingly demanding AI workloads.”
The expansion also addresses a growing infrastructure challenge as AI systems increasingly perform tasks between interactions with large language models.
AI agents can execute code, retrieve information and call external tools, activities that rely heavily on CPUs. Delays in those operations can leave GPUs idle while they wait for the next request, reducing the efficiency of expensive computing infrastructure.
Oracle said its Vera CPU offering is designed to accelerate those operations through high single-thread performance and memory bandwidth. Its Kubernetes service will allow customers to scale CPU and GPU resources independently, while Oracle Acceleron networking provides hardware-based isolation for workloads executing untrusted, AI-generated code.
“NVIDIA Vera CPUs on OCI deliver the world-class loaded performance needed to execute code and run tools across our rapidly growing agentic sandbox workloads,” said Uday Ruddarraju, chief technology officer of compute at OpenAI. “We are bringing Vera into production on OCI to support these workloads at scale.”
Oracle said customers could adjust computing resources to match their workloads, potentially reducing idle capacity and improving the utilisation of infrastructure investments.
“Oracle Cloud Infrastructure gives customers the performance, security and scale to advance frontier AI,” said Mahesh Thiagarajan, president of Oracle Cloud Infrastructure at Oracle. “Our collaboration with NVIDIA extends those capabilities across training, inference and agentic AI. By combining NVIDIA Vera Rubin GPUs and Vera CPUs with Oracle Acceleron networking and AI-optimized data centers, we’re helping customers keep GPUs productive, secure and scale efficiently as their needs grow.”
Nvidia has been investing in accelerated computing systems that combine processors, networking and software to support increasingly complex AI workloads. Its CUDA software platform is designed to help developers run applications across successive generations of Nvidia hardware.
“AI factories must be productive, durable and fungible — delivering efficient computing, remaining useful through continued software advances and serving different models and workloads as demand changes,” said Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA. “With Oracle, we’re bringing Vera Rubin and Vera CPUs to OCI to help customers put more of their infrastructure to work today and sustain its value as AI evolves.”
The companies did not disclose the investment value, deployment timetable or specific locations for the planned multi-gigawatt expansion in the announcement.
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