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Arm expands compute platform to silicon products in historic company first

Arm expands compute platform to silicon products in historic company first

Enterprise & IT Mar 26,2026 0

Arm Holdings plc (NASDAQ: ARM) today announced the next evolution of the Arm compute platform, extending into production silicon products for the first time in the company’s history. This begins with the launch of the Arm AGI CPU, an Arm-designed CPU for AI data centers, built to address a rising class of agentic AI workloads.

For more than three decades, the industry has innovated on the Arm compute platform to deliver scalable, power-efficient computing across hundreds of billions of devices. As AI transforms global computing infrastructure, partners across the ecosystem are asking for ways to deploy Arm technology at scale. In response, Arm is expanding its platform strategy beyond IP and Compute Subsystems (CSS) to include Arm-designed silicon products – giving partners the broadest set of options to build on Arm and enabling faster innovation across the AI ecosystem.

“AI has fundamentally redefined how computing is built and deployed. Agentic computing is accelerating that change,” said Rene Haas, CEO, Arm. “Today marks the next phase of the Arm compute platform and a defining moment for our company. With the expansion into delivering production silicon with our Arm AGI CPU, we are giving partners more choices all built on Arm’s foundation of high-performance, power-efficient computing, to support agentic AI infrastructure at global scale.”

Agentic AI is reshaping AI infrastructure, driving more demand for CPUs
The rise of AI agents is driving a major inflection point in global computing. As AI shifts from training models to deploying continuously running agents that reason, plan and act, the volume of tokens generated across AI systems is rapidly increasing and requires significantly more CPUs to handle reasoning, coordination and data movement.

As organizations scale agent-driven applications, data centers are expected to require more than 4x the current CPU capacity per GW* — driving the need for significantly more compute within the same power envelope. This is driving demand for a new class of CPUs designed for AI-scale infrastructure — delivering the performance needed to sustain high token throughput, the efficiency required to operate within real-world power constraints and a simplified architecture built without the overhead and complexity of x86 processors.

Extending the Arm platform into production silicon
To help partners move faster in this new environment, Arm is introducing the Arm AGI CPU, which is expected to be the foundation for agentic data centers. The expansion into silicon products provides the ecosystem with greater flexibility in how they build and deploy Arm-based infrastructure — whether licensing Arm IP, adopting Arm CSS, or deploying Arm-designed silicon.

The Arm AGI CPU delivers:

Performance: Up to 136 Arm Neoverse V3 cores per CPU, delivering leading performance per core, SoC, blade and rack*, with 6GB/s memory bandwidth per core at sub-100ns latency.
Scale: 300-watt TDP with a dedicated core per program thread enables deterministic performance under sustained load, eliminating throttling and idle threads.
Efficiency: Supports high-density 1U server chassis that supports air-cooled deployments with up to 8,160 cores per rack, and liquid-cooled systems delivering 45,000+ cores per rack.
These capabilities translate into greater workload density, improved accelerator utilization and more usable compute within existing power envelopes — critical advantages as AI infrastructure scales. The Arm AGI CPU delivers more than 2x performance per rack versus x86 CPUs, enabling up to $10B in CAPEX savings per GW of AI data center capacity*.

Broad ecosystem support for Arm AGI CPU
Meta serves as the lead partner and co-developer, leveraging Arm AGI CPU to optimize infrastructure for its family of apps and working alongside Meta’s own custom silicon, called Meta Training and Inference Accelerator (MTIA), enabling more efficient orchestration in large-scale AI systems. Arm and Meta are committed to collaborating across multiple generations of the Arm AGI CPU roadmap.

“Delivering AI experiences at global scale demands a robust and adaptable portfolio of custom silicon solutions, purpose-built to accelerate AI workloads and optimize performance across Meta’s platforms,” said Santosh Janardhan, head of infrastructure, Meta. “We worked alongside Arm to develop the Arm AGI CPU to deploy an efficient compute platform that significantly improves our data center performance density and supports a multi-generation roadmap for our evolving AI systems.”

Alongside Meta, Arm has confirmed additional commercial momentum with partners including Cerebras, Cloudflare, F5, OpenAI, Positron, Rebellions, SAP, and SK Telecom. These customers will deploy the Arm AGI CPU for key agentic CPU use-cases including accelerator management, control plane processing, and cloud and enterprise-based API, task and application hosting.

To accelerate this ramp, Arm is partnering with lead OEMs and ODMs including ASRock Rack, Lenovo, Quanta Computer, and Supermicro, with early systems available now and broader availability expected in the second half of the year.

More than 50 leading companies across hyperscale, cloud, silicon, memory, networking, software, system design and manufacturing are supporting the expansion of the Arm compute platform into silicon. That momentum includes industry leaders such as AWS, Broadcom, Google, Marvell, Micron, Microsoft, NVIDIA, Samsung, SK hynix and TSMC, alongside many others.

A new era for the Arm compute platform
For decades, the industry has built on the Arm compute platform through its industry-leading IP and, more recently, Arm CSS, grounded in a foundation of high-performance, power-efficient computing. The expansion into production silicon with the Arm AGI CPU marks the next phase of that evolution, extending Arm into data center silicon and bringing its power-efficient architecture to AI infrastructure at scale.

Tags: ARM
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