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Nvidia Posts $81.6B Quarter, Bets $200B on Agentic AI with Vera CPU

Mason

22 May 2026 — 1 min read

Nvidia shattered expectations with a record $81.6 billion in first-quarter revenue, driven by $75.2 billion in data center sales, as CEO Jensen Huang unveiled the Vera CPU specifically engineered for agentic AI workloads. The company guided $91 billion for next quarter, while its private holdings nearly doubled to $43 billion, with $30 billion committed to OpenAI, signaling a strategic pivot from GPU training dominance to CPU inference supremacy in an emerging $200 billion market.

Vera CPU: Targeted at a $200B Agentic AI Compute Market

Jensen Huang introduced the Vera processor, a purpose-built CPU designed to dominate inference tasks in agentic AI systems. Standalone Vera sales have already hit $20 billion this year, underscoring immediate market traction. Huang projects a $200 billion total addressable market for agentic AI compute, where CPUs are expected to lead inference workloads due to their efficiency in handling sequential reasoning and real-time decision-making.

Record Revenue and Strategic Capital Deployment

Nvidia's first-quarter data center revenue of $75.2 billion contributed to the overall record of $81.6 billion, with next-quarter guidance surging to $91 billion. The company's private holdings nearly doubled to $43 billion, including a $30 billion commitment to OpenAI, reflecting deepening integration with leading AI labs. Meanwhile, the Blackwell architecture has been adopted by all major hyperscalers, cementing Nvidia’s infrastructure role even as the inference shift reshapes chip demand.

The transition from GPU-heavy training to CPU-centric inference for agentic AI represents a strategic expansion of Nvidia’s addressable market. By positioning Vera as the inference backbone for autonomous AI agents, Nvidia could potentially double its TAM, leveraging Vera’s low-latency processing to capture the next wave of enterprise AI deployments. This move mirrors the industry’s gradual realization that real-time agentic systems require specialized silicon beyond general-purpose GPUs.

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