Vera Arrives: NVIDIA’s First CPU Built for Agents Lands at Top AI Labs

NVIDIA hand-delivered its first Vera CPUs to Anthropic, OpenAI, and SpaceXAI, followed by Oracle Cloud Infrastructure — an 88-core custom processor purpose-built for agentic AI workloads.

Monday May 18, 2026 Source: nvidia.com
TL;DR — Quick Answer

NVIDIA's first custom CPU, Vera, began shipping, with Vice President of Hyperscale and HPC Ian Buck hand-delivering the opening systems to three leading AI labs — Anthropic in San Francisco, OpenAI at Mission Bay, and SpaceXAI in Palo Alto — on Friday, followed by Oracle Cloud Infrastructure in Santa Clara on Monday. Vera packs 88 custom NVIDIA-designed Olympus cores, 1.2 TB/s of memory bandwidth, and up to 1.8x faster per-core performance on agentic AI workloads, handling orchestration, tool-calling, agent sandboxing, and long-context state that GPUs alone cannot run. It also serves as the host processor for the Vera Rubin NVL72. OCI, the first hyperscale cloud to deploy Vera, plans to field hundreds of thousands of Vera CPUs beginning in 2026.

Key Takeaways

Vera Arrives: NVIDIA’s First CPU Built for Agents Lands at Top AI Labs — AI news article illustration

Vera is here. NVIDIA announced that its first custom CPU, built from the ground up for agentic AI, is shipping — and that Vice President of Hyperscale and HPC Ian Buck personally hand-delivered the opening systems to three of the world’s leading AI labs.

The Deliveries

NVIDIA Vice President of Hyperscale and HPC Ian Buck hand-delivered Vera CPU systems across the AI ecosystem on Friday: Anthropic in San Francisco, OpenAI at Mission Bay, and SpaceXAI in Palo Alto, followed by a delivery to Oracle Cloud Infrastructure in Santa Clara the following Monday.

Why a CPU for Agents

The pitch is simple: AI agents do not run on GPUs alone. Every agentic sandbox, every tool call, every orchestration layer, and every long-context retrieval operation is CPU work. A gauntlet of concurrent, real-time tasks puts pressure on CPUs in ways traditional core-density-focused designs were never built to prioritize.

“Agentic AI is creating a new CPU moment in the AI factory — as models move from answering to acting, Vera is purpose-built to keep that work moving at scale,” Buck said.

Vera at a Glance

The specs underline the new class:

What Vera’s First Customers Said

SpaceXAI is evaluating Vera for reinforcement learning workloads and the agent-based simulation pipelines behind its training stack. OCI — the first cloud to deploy Vera at hyperscale — plans to deploy hundreds of thousands of Vera CPUs beginning in 2026. “Vera’s architecture is purpose-built for high-throughput reasoning workloads,” said OCI’s Karan Batta.

What This Means

Vera marks NVIDIA’s entry as an x86 and Arm competing CPU designer and its bet that agentic AI — not just training — is the next infrastructure battleground. For the AI labs now running it, the question is whether the CPU that keeps up with the AI factory becomes the default host for the age of agents.

Frequently Asked Questions

What is the NVIDIA Vera CPU?

Vera is NVIDIA's first custom CPU, purpose-built for agentic AI, with 88 custom Olympus cores, 1.2 TB/s of memory bandwidth, and up to 1.8x faster per-core performance on agentic workloads.

Which companies received the first Vera CPUs?

NVIDIA hand-delivered the first Vera CPU systems to Anthropic, OpenAI, and SpaceXAI, followed by Oracle Cloud Infrastructure, with AWS receiving a Vera server later in the rollout.

Why does agentic AI need a new CPU?

AI agents run heavily on CPU work — orchestration, tool calls, sandboxes, and long-context retrieval — and Vera is designed from the ground up for that concurrent real-time workload that traditional CPUs were not built to prioritize.

What does Vera do in the Vera Rubin NVL72?

Vera is the host processor for the Vera Rubin NVL72, pairing with Rubin GPUs over second-generation NVLink-C2C and sharing a unified memory architecture that keeps accelerated compute highly utilized.

This article is based on the official announcement from nvidia.com . Read the original for full technical details.

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