Arm has introduced the Arm AGI CPU, a processor designed to manage orchestration, data movement and system behavior across artificial intelligence infrastructure as workloads shift from isolated inference tasks to coordinated agentic workflows. The CPU emphasizes high core scalability, memory bandwidth and system-level efficiency, enabling coordination across CPUs, GPUs and other accelerators in large-scale deployments.

At the 2026 OCP EMEA Summit, Arm announced that Verda, a European cloud provider, will deploy the Arm AGI CPU for agentic AI orchestration alongside NVIDIA GB300-based systems and upcoming NVIDIA Vera Rubin-based systems. This deployment reflects a broader industry shift toward tightly integrated CPU-accelerator architectures where CPUs play a central role in enabling scalable, efficient AI systems.

Meta Collaboration on Scalable Infrastructure

Arm’s work on the AGI CPU aligns with leading hyperscalers shaping the future of AI infrastructure. Meta serves as a lead partner and customer, collaborating on building scalable, open platforms capable of supporting increasingly complex AI workloads. The partnership focuses on system-wide efficiency and interoperability as critical factors in scaling workloads effectively.

Arm and Meta are advancing infrastructure that enables more efficient orchestration and deployment of agentic AI. This collaboration underscores a broader industry shift as hyperscalers move toward tightly integrated systems where CPUs play a central role in managing AI workflows. By collaborating on open architectures and system-level design principles, the companies are helping define the foundation for next-generation AI infrastructure.

Verda’s Integrated System Architecture

Verda’s deployment shows how next-generation AI systems are being built in practice. By combining Arm-based CPU infrastructure with NVIDIA GB300 GPU platforms, Verda enables a tightly coupled architecture designed to support agentic AI workloads at scale. In this model, accelerators deliver the performance required for model execution, while the CPU orchestrates workflows and manages data movement across components.

Ruben Bryon, Founder and CEO of Verda, stated, “At Verda, we’re operating a renewable-powered AI cloud built for ML teams. By pairing Arm AGI CPU with our NVIDIA GB300 and upcoming VR200 fleet, we aim to deliver a fully Arm-native stack from orchestration to inference, giving customers the density and efficiency that agentic AI demands at scale.”

Open Standards Through OCP Contributions

Arm is contributing multiple specification proposals to the Open Compute Project (OCP) to enable alignment across the ecosystem and reduce friction for partners building Arm-based AI infrastructure. These contributions span three key areas: day zero deployment readiness, reference designs for faster adoption, and support for an open chiplet ecosystem.

Day zero deployment readiness includes advancing system architecture specifications within OCP, including Server Base System Architecture (SBSA), Server Base Manageability Requirements (SBMR) and the Arm Data Center Architecture Compliance (ADAC) framework. These provide a consistent foundation for hardware platforms, system management and validation, enabling operating systems and applications to run unmodified across implementations.

For faster adoption, Arm is contributing reference server designs for Arm AGI CPU-based systems. These include server hardware specifications and firmware development frameworks that provide a production-ready foundation for partners. By standardizing key elements of system design while preserving flexibility for differentiation, these contributions simplify development and enable faster, more efficient deployment across a range of use cases.

Through its Foundation Chiplet System Architecture (FCSA) work with OCP and ecosystem partners, Arm is helping enable a more open and interoperable chiplet ecosystem. This approach supports modular system design and reduces integration complexity, allowing partners to more efficiently develop and deploy AI-optimized silicon platforms.

Industry Shift to CPU-Centric AI Infrastructure

Traditional AI pipelines follow a relatively linear path: data in, inference out. Agentic systems are fundamentally different. They plan, reason and act, often through continuous loops spanning multiple models, services and decision points. This shift drives a step-change in infrastructure demands.

Accelerators continue to execute model workloads and generate tokens, but CPUs are increasingly responsible for coordinating these activities across the system. As systems expand, consistency across hardware platforms and system management becomes critical. Standardized architectures ensure complex, multi-agent workloads can run reliably across diverse environments without requiring custom integration.

Paul Saab, software engineer at Meta, said, “As AI infrastructure scales, standardization across the stack becomes increasingly important to enable interoperability and efficiency. Our collaboration with Arm reflects a shared focus on advancing open platforms that can support large-scale AI workloads.”

George Tchaparian, CEO of the Open Compute Project, stated, “OCP brings together a global community to accelerate innovation through open collaboration. Contributions across areas such as chiplets, system readiness and reference designs are key to enabling broader adoption of open AI infrastructure.”