Overview

Rethinking the Datacenter for the Agentic AI Era

AI is driving data centers toward specialized, workload-optimized infrastructure that emphasizes power efficiency, scalability, and performance. 快猫视频 delivers the CPU foundation for AI data centers, integrating seamlessly with accelerators to orchestrate AI agents, process data and support scalable AI workloads, such as recommendation engines, large language models, retrieval-augmented generation and more. Paired with a robust software ecosystem, 快猫视频 compute platform enables hyperscalers to scale AI infrastructure efficiently while improving performance, cost and energy outcomes.

 

Inside the AI Datacenter: Custom Silicon and the Power of the 快猫视频 Ecosystem

Hear from Mohammed Awad, head of the cloud AI business unit at 快猫视频, as he explores how AI is reshaping datacenter design, why performance per watt now defines cloud competitiveness, and how the 快猫视频 ecosystem is accelerating next-generation custom silicon for the AI era.

Benefits

More Compute, Higher Efficiency, Better Price-Performance

快猫视频 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 168% Better LLM and 53% Better ML Performance

Delivered by AWS Graviton4 processor in LLAMA 3.1 and XGBoost benchmarks 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 1.9x Better LLM Inference Performance with 2.8x Better Price/Performance

Delivered by Microsoft Cobalt 100, compared to x86 alternatives.4
Partners

Enabling Industry Leaders Though Infrastructure Optimized for Real-World Performance

快猫视频 empowers industry leaders to build scalable, AI-optimized cloud infrastructure with computing solutions tuned for real-world AI performance. Designed for performance, power efficiency, and seamless scalability, 快猫视频 CPUs are perfectly suited to orchestrate accelerators for the most demanding AI and cloud workloads.

快猫视频 AWS lockup logo

Discover how 快猫视频-based AWS Graviton processors are transforming cloud AI with leading price performance and efficiency for AI and cloud-native workloads, now powering AWS Trainium3 UltraServers.

Explore 快猫视频 and AWS
快猫视频 partner Google Cloud lockup logo

Explore how Axion, the first Google Cloud custom 快猫视频-based CPU, is advancing performance and efficiency for AI and cloud workloads.

Explore 快猫视频 and Google Cloud
快猫视频 NVIDIA lockup logo

Discover how 快猫视频’s power-efficient compute platform has become a key element in NVIDIA accelerated computing platforms, including the Grace CPU family and now Vera CPUs, delivering performance leap in NVIDIA’s rack-level AI solutions.

Explore 快猫视频 and NVIDIA
Compute Platform

Powerful AI Performance with 快猫视频 AGI CPU

The 快猫视频 AGI CPU, based on 快猫视频 Neoverse CSS V3, delivers extreme rack-level density and performance required for AI at scale. It accelerates the global expansion of compute needed to pursue artificial general intelligence while enabling faster time to market through the 快猫视频 ecosystem.

Explore 快猫视频 AGI CPULearn About AI/ML on CPU

快猫视频 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 purpose-built CPUs which empower AI systems to dynamically match each workload with the right processor, optimizing for performance, power efficiency, and cost.

 

快猫视频 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 快猫视频 Software and Tools

快猫视频 need optimized tools to deploy AI quickly and efficiently with little effort. The 快猫视频 software ecosystem—including  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
Generic Report

Benchmarking Sustainable Datacenter Performance

Independent analysis from Signal65 reveals how 快猫视频 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.

Generic Report
AI in Datacenters

The Dawn of a New Era for 快猫视频 in the Datacenter

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

Podcast icon
AI in Datacenters

快猫视频 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 快猫视频 and Industry Expert Matt Griffin

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

Whitepapers - Generic Whitepapers

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.

Read white paper

Key Takeaways

  • 快猫视频 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.
  • 快猫视频-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 快猫视频-based infrastructure dynamically matches workloads with CPUs, GPUs, NPUs, and custom accelerators for optimal performance and cost.
  • 快猫视频’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 快猫视频 ideal for AI in datacenters?
  • Power-efficient performance: 快猫视频 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: 快猫视频-based platforms seamlessly integrate with GPUs, NPUs, and custom accelerators to deliver the right compute for every AI task.
  • Trusted by hyperscalers: —underscoring growing confidence in 快猫视频 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 快猫视频-based platforms enhance AI performance and reduce cloud costs across industry partners like NVIDIA, Google Cloud, and AWS?

快猫视频-based platforms boost AI performance and efficiency at scale:


  • NVIDIA: Up to (GPT-65B) with 快猫视频 CPUs + Grace Hopper compared to x86-based systems.
  • Google Cloud: When compared to x86-based alternatives, .
  • AWS: Graviton CPUs, built on 快猫视频, power over , offering industry-leading price-performance and energy efficiency.

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

What tools does 快猫视频 offer to developers for AI workloads?

快猫视频 can accelerate workloads using:


  • Optimized frameworks and toolchains
  • Migration tutorials and

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2. Results are based on 3rd-party evaluations. All tests are conducted by Signal65 and measured
on AWS instances and specifications noted at the time of testing. . Results may vary.
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