Overview

Rethinking the Datacenter for the AI Era

AI Summary

AI is driving datacenters toward specialized, workload-optimized infrastructure that emphasizes power efficiency, scalability, and performance. Arm delivers a flexible compute foundation with Neoverse CPUs that integrate seamlessly with accelerators to support AI workloads such as recommendation engines, large language models, and retrieval-augmented generation. Paired with robust developer tools, this platform enables hyperscalers and cloud providers to scale AI efficiently while lowering costs.

Download eBook
Benefits

More Compute, Higher Efficiency, Better Price-Performance

Arm delivers energy-efficient compute that pairs seamlessly with a broad range of AI accelerators—helping you achieve strong performance and efficiency while lowering total cost of ownership.

Up to 8x Faster ML Model Training and 4.5x LLM inference Performance

Delivered by the NVIDIA Grace Hopper Superchip when training a DLRM model and inferencing GPT-65B model, compared to x86+Hopper systems.1

Up to 3x Better Recommender Performance

Delivered by Google Axion processor in MLPerf DLRMv2 benchmark compared to x86 alternatives.2

Up to 2.5x Higher AI Inference Performance

Delivered by Google Axion processor, with 64% cost savings and faster RAG for real-time AI compared to x86 alternatives.3

Up to 2x Better Performance with LLM and ML Inference Tasks

Delivered by Axion-based VMs compared to current-generation x86 instances.4

Partners

Enabling Industry Leaders Though Infrastructure Optimized for Real-World Performance

Arm empowers industry leaders to build a new wave of scalable, efficient data centers with computing solutions optimized for real-world performance. Designed for performance, power efficiency, and seamless scalability, Arm CPUs are perfectly suited to pair with accelerators for the most demanding AI and cloud workloads.

Arm and AWS

Discover how Arm-based AWS Graviton processors are transforming cloud computing with leading price performance and efficiency for AI and cloud-native workloads, now powering over 50% of AWS recent CPU capacity.

Explore how Axion, the first Google Cloud custom Arm-based CPU, is advancing performance and efficiency for AI and cloud workloads, with up to 2x better performance than current x86 instances.

Arm and NVIDIA

Discover how Arm’s power-efficient compute platform has become a key element in NVIDIA accelerated computing platforms, including the Grace CPU family, delivering up to a 10x performance leap in AI tasks.

Compute Platform

Powerful AI/ML Performance with Arm Neoverse

Designed to handle demanding AI workloads efficiently, Arm Neoverse CPUs deliver high throughput, power efficiency, and low TCO—making them ideal when CPUs are the practical choice. From recommendation engines and language model inference to retrieval-augmented generation (RAG), Neoverse scales across a broad range of AI applications.

Performance

Up to 3x better recommendation model performance on Google Axion vs. x86 2.

cost saving

Up to 2.5x higher AI inference throughput with 64% cost savings compared to x86 alternatives 5.

Ecosystem

Broad hyperscaler adoption and multi-cloud availability.

Explore Arm Neoverse for AI WorkloadsLearn About AI/ML on CPU

Arm Compute Platform for Every AI Workload

As AI progresses from classic machine learning to generative AI and now agentic models, workloads are becoming increasingly compute and power intensive. Meeting these demands requires a shift to heterogeneous infrastructure which enables systems to dynamically match each workload with the right processor, optimizing for performance, power efficiency, and cost.

 

Arm Neoverse CPUs provide a power-efficient, scalable compute platform that integrates seamlessly with GPUs, NPUs and custom accelerators and delivers increased performance, flexibility, efficiency, and scalability.

Explore Heterogeneous Computing Solutions
Software and Developer Tools

Optimize AI Workloads with Arm Software and Tools

Developers need optimized tools to deploy AI quickly and efficiently with little effort. The Arm software ecosystem—including Arm Kleidi libraries and broad framework support—helps accelerate time to deployment and boost AI workload performance across cloud and edge.

Resources

Latest News and Resources

  • NEWS and BLOGS
  • Report
  • Podcasts
  • White paper

Benchmarking Sustainable Datacenter Performance

Independent analysis from Signal65 reveals how Arm Neoverse-based AWS Graviton4 processors consistently deliver superior performance per watt across web, database, and AI workloads—driving greater efficiency and lower total cost of ownership in datacenters.

AI in Datacenters

The Dawn of a New Era for Arm in the Datacenter

Industry analyst Ben Bajarin explores how AI is redefining datacenter architecture and why Arm is emerging as a key player in powering scalable, efficient infrastructure for the AI era.

Podcast icon
AI in Datacenters

Arm and NVIDIA Redefine AI in Datacenters

Listen to our podcast with NVIDIA to explore how our partnership is transforming enterprise computing.

Podcast icon
AI in Datacenters

The Future of AI Infrastructure with Arm and Industry Expert Matt Griffin

Hear Arm and Matt Griffin, founder of the 311 Institute, discuss emerging AI infrastructure trends, challenges in scaling compute, and how Arm is enabling efficient, sustainable AI from cloud to edge.

Build a Scalable AI Platform from Cloud to Edge

Learn five decisions that help enterprises design a future-ready compute stack. Explore how to embrace heterogeneous compute, unify the software layer, and align infrastructure with business goals to cut latency and scale efficiently across environments.

Key Takeaways

Key Takeaways

  • Arm enables datacenter transformation from general-purpose platforms to specialized, workload-optimized AI infrastructure built for efficiency and scalability.
  • Neoverse CPUs deliver high throughput, power efficiency, and lower TCO for AI applications including recommendation engines and large language model inference.
  • Arm-based processors from partners like Google, AWS, Microsoft and NVIDIA achieve up to 8x training and 4.5x inference performance gains over x86 systems.
  • Heterogeneous Arm-based infrastructure dynamically matches workloads with CPUs, GPUs, NPUs, and custom accelerators for optimal performance and cost.
  • Arm’s Kleidi libraries, frameworks, and developer tools streamline AI deployment and workload optimization across cloud and edge environments.

Frequently Asked Questions: AI in the Datacenter

What makes Arm ideal for AI in datacenters?

  • Power-efficient performance: Arm Neoverse CPUs deliver industry-leading performance-per-watt, reducing energy costs and improving operational efficiency.
  • Lower total cost of ownership (TCO): Scalable architectures optimized for modern AI workloads help businesses reduce infrastructure spend.
  • Flexible, workload-optimized systems: Arm-based platforms seamlessly integrate with GPUs, NPUs, and custom accelerators to deliver the right compute for every AI task.
  • Trusted by hyperscalers: By 2025, half of compute shipped to top hyperscalers is projected to be Arm-based—underscoring growing confidence in Arm for large-scale AI deployment.
  • Unified AI infrastructure: A mature software ecosystem and broad adoption support seamless integration across diverse compute engines in cloud and datacenter environments

How do Arm-based platforms enhance AI performance and reduce cloud costs across industry partners like NVIDIA, Google Cloud, and AWS?

Arm-based platforms boost AI performance and efficiency at scale:


Together, these innovations enable faster, more cost-effective AI across cloud and hyperscale platforms.

What tools does Arm offer to developers for AI workloads?

Developers can accelerate workloads using:


Stay Connected

Subscribe to stay up to date on the latest news, trends, case studies, and technology insights.