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Nvidia Wants to Own Every Chip Inside AI Data Centers
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Nvidia has unveiled new performance benchmarks for its upcoming Vera Rubin chip system, signalling a strategic shift from being purely a maker of graphics processing units (GPUs) towards positioning itself as a supplier of complete AI computing systems, including central processing units (CPUs). The move comes as the AI industry increasingly relies on more complex, agentic systems, which demand CPUs capable of orchestrating data flows and networking alongside the GPUs that handle model training and inference. The announcement, made at a technical workshop in Santa Clara, comes just ahead of rival AMD's own product event in San Francisco.
Vera Rubin is the successor to Nvidia's Grace Blackwell system and pairs one Vera CPU with every two Rubin GPUs, with a full NVL72 rack containing 36 CPUs and 72 GPUs. Nvidia claims the new system processes ten times more tokens per watt than Grace Blackwell, offers nearly triple the memory bandwidth, and requires far fewer cables, potentially cutting rack installation time from hours to minutes. OpenAI is reportedly already using one such rack, while Nvidia says standalone Vera CPUs could reach Chinese customers as soon as August; the briefings were led by vice president Ian Buck rather than chief executive Jensen Huang, who was in Japan announcing separate robotics partnerships.
In short
- Nvidia unveils Vera Rubin chip system, expanding beyond GPUs into CPUs.
- System claims 10x efficiency gains and triple the memory bandwidth of predecessor.
- OpenAI already using a Vera Rubin rack; wider rollout expected soon.
Steelman: both sides, in good faith
The strongest fair case each way — we don't pick a winner.
The case for
Nvidia's integration of CPUs with its GPUs reflects sound business strategy that delivers tangible technical advantages. Designing complementary components together enables superior efficiency, as demonstrated by substantial performance improvements and simplified deployment, whilst meeting genuine market demand for tightly coordinated AI infrastructure. Vertical integration is standard practice across technology sectors and benefits customers through seamless system integration rather than piecing together components from competing vendors.
The case against
Nvidia's pivot towards complete systems is troubling given its existing GPU market dominance. By bundling CPUs with its dominant processors, Nvidia leverages market power in one sector to gain advantage in another, limiting customers' ability to select best-of-breed components from competing suppliers. This integration increases customer lock-in and reduces the competitive pressure that drives innovation, raising legitimate antitrust questions about whether one company should control all critical layers of AI infrastructure.
Explained simply
Nvidia is a leading maker of computer chips used in artificial intelligence systems. For years, it specialised in graphics processing units (GPUs), which perform the intensive calculations needed to train and run AI models. Now it is expanding beyond this, moving towards supplying complete AI computing systems that combine GPUs with central processing units (CPUs).
Artificial intelligence data centres have traditionally relied mainly on GPUs for nearly all their heavy computational work. As AI systems have grown more complex and autonomous, they increasingly need CPUs to coordinate the overall system, managing data flows, controlling networks and orchestrating how different components work together. This means data centre operators need both types of chip working in tandem, creating an opportunity for companies like Nvidia to supply complete systems rather than individual components.
Whoever dominates the chips inside AI data centres wields considerable influence over how the technology develops and who profits from it. Nvidia already holds a commanding position in the GPU market, and by also supplying CPUs, it would deepen its control over the entire computing infrastructure. This strategic move comes as competition intensifies, with rival chipmaker AMD preparing its own competing systems, making control of AI data centre infrastructure increasingly central to the technology industry's future.
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