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Oracle has taken a giant leap in the AI infrastructure race by launching and optimizing its first wave of NVIDIA GB200 NVL72 racks in its global data centers. These liquid-cooled supercomputing units, packed with the latest NVIDIA Blackwell GPUs, are now operational and ready to drive next-generation AI development on both NVIDIA DGX Cloud and Oracle Cloud Infrastructure (OCI).
These cutting-edge systems are purpose-built to support advanced reasoning models and agent-based AI applications. Leveraging the power of NVIDIA’s GB200 Grace Blackwell architecture, Oracle is not only accelerating access to high-performance AI computing but also reshaping how data centers operate at scale.
The Next Frontier in Cloud AI Infrastructure
Oracle is now operating thousands of NVIDIA Blackwell GPUs through the GB200 NVL72 platform—a rack-scale AI system combining 36 Grace CPUs and 72 Blackwell GPUs per rack. This setup is a part of a larger push to build one of the world’s most powerful AI computing clusters.
With high-speed NVIDIA Quantum-2 InfiniBand and Spectrum-X Ethernet networking, these new AI factories offer ultra-low latency and scalability across thousands of GPUs. Oracle’s deployment sets the stage for next-gen AI workloads, from natural language processing and machine reasoning to autonomous systems and semiconductor design.
Here are the key highlights of Oracle’s deployment:
- Liquid-Cooled GPU Racks Live at Scale: Thousands of NVIDIA Blackwell GPUs are now operational at OCI, ready to serve enterprise AI and agentic reasoning tasks.
- Part of NVIDIA DGX Cloud: These systems are integrated into the DGX Cloud stack, enabling seamless development, deployment, and scaling of AI workloads.
- Optimized for Reasoning Models and AI Agents: New workloads like multi-step reasoning, AI-driven decision-making, and autonomous systems stand to benefit from the GB200 NVL72’s architecture.
- OCI’s Massive AI Push: Oracle is positioning OCI to become home to one of the world’s largest GPU clusters, potentially exceeding 100,000 Blackwell GPUs.
- Diverse Use Cases: From chip design and autonomous driving to LLM training and inference token generation, the racks support a vast array of AI innovations.
- Advanced Networking Stack: NVIDIA’s cutting-edge networking enables high-throughput, low-latency communication between GPUs, essential for high-speed training and inference.
- Flexible Deployment: OCI’s offerings span public, government, and sovereign clouds, plus customer-owned data centers through OCI Dedicated Region and OCI Alloy.
- Immediate Enterprise Use: Leading tech companies, governments, and cloud providers are already lining up to deploy workloads on OCI’s Blackwell infrastructure.
Oracle’s move comes amid a flurry of new AI model releases by industry giants, highlighting the ongoing demand for infrastructure capable of training and serving large-scale, complex models. This deployment demonstrates not just Oracle’s commitment to AI, but its intent to compete fiercely with other hyperscalers like AWS, Azure, and Google Cloud.
What Undercode Say:
Oracle’s strategic deployment of NVIDIA GB200 NVL72 systems marks a tectonic shift in how AI infrastructure will be provisioned in the cloud era. This is not just another upgrade—it’s the backbone of AI’s next phase.
- Vertical Integration Strategy: Oracle is clearly aligning itself with NVIDIA’s full-stack approach. By combining hardware, software, and networking into a single ecosystem, Oracle gains tighter control over performance and scalability.
Blackwell’s Real-World Debut: While NVIDIA’s Blackwell chips were announced with much fanfare, Oracle’s rollout represents the first significant, high-scale implementation of the architecture. It’s a proof-of-concept turned production at hyperscale.
AI Factories Become Real: The term “AI factories” isn’t just a metaphor anymore. These are actual data centers optimized for generating AI intelligence, akin to how factories once powered the industrial age.
Inference Tokens Drive Infrastructure: Oracle’s emphasis on meeting “inference token” demand suggests an awareness of the compute requirements of post-training AI workloads—an area often overlooked compared to raw training power.
OCI’s Competitive Edge Grows: Historically seen as the underdog, OCI’s aggressive push into AI infrastructure may reshape market perceptions. OCI is no longer playing catch-up—it’s building future-ready infrastructure before many rivals.
NVIDIA Ecosystem Magnetism: With OCI among the first to offer production-ready Blackwell infrastructure, NVIDIA benefits too. It reinforces NVIDIA’s strategy of scaling through partners instead of building its own hyperscale cloud.
Cooling and Sustainability: Liquid cooling isn’t just a performance booster—it’s also a sustainability move. Oracle can significantly reduce energy usage and thermal waste, improving both economics and environmental footprint.
Decentralized Deployment Options: With options like OCI Alloy and Dedicated Region, Oracle is hedging against regulatory and sovereignty concerns—vital as more countries demand in-country AI compute.
Readiness for Agentic AI: Blackwell is optimized for AI agents that require real-time interaction, decision trees, and dynamic reasoning. Oracle’s racks are well-aligned to support this emerging AI paradigm.
Cross-Cloud and Hybrid Future: Oracle’s investment aligns with a hybrid future where workloads are split across multiple clouds and on-prem. Its ability to support varied deployment models makes it a more attractive long-term partner.
As more enterprises dive into AI, availability of scalable infrastructure like GB200 NVL72 becomes a competitive differentiator. Oracle’s head start may give it leverage in securing top-tier AI clients and research partners.
Fact Checker Results:
- Confirmed Deployment: Oracle and NVIDIA have officially announced the deployment of GB200 NVL72 systems.
- AI Model Compatibility: Blackwell GPUs are optimized for reasoning models and agent-based AI, aligning with Oracle’s intended use.
- OCI Expansion Plans: Verified that Oracle is planning Blackwell clusters scaling beyond 100,000 GPUs.
References:
Reported By: blogs.nvidia.com
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