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AI doesn’t operate on illusion—it thrives on staggering computational infrastructure. At the heart of this digital transformation are purpose-built AI data centers: massive, high-efficiency facilities loaded with tens of thousands of GPUs, specialized silicon, and ultra-fast network architecture. These systems are engineered to handle the colossal demands of training large language models (LLMs), executing real-time inference, and powering next-generation simulations.
These aren’t your average server farms—they’re the digital engines of progress. In a bold example of scale, Meta has announced plans for AI-focused data center campuses so large, one will rival the footprint of Manhattan. The upcoming Hyperion site in Louisiana is expected to reach 5 gigawatts, becoming one of the largest AI infrastructure projects in history.
1. Equinix IBX Facilities (Global)
With over 260 International Business Exchange locations across 70 global cities, Equinix leads in providing high-density GPU hosting. Featuring direct-to-chip liquid cooling in over 100 facilities, Equinix delivers up to 25% more energy efficiency, enabling seamless access to NVIDIA DGX and HGX nodes for enterprise AI workloads.
2. Digital Realty (Global)
Operating 170 data centers worldwide, Digital Realty specializes in high-powered racks (30 kW–150 kW) supported by advanced cooling. Their Private AI Exchange (AIPx) and ServiceFabric® infrastructure reduce latency by up to 40%, bridging local GPU clusters with public cloud access.
3. NTT Global Data Centers (APAC, EMEA, Americas)
NTT’s facilities offer cutting-edge liquid immersion and direct-contact cooling—improving energy efficiency by around 30%. With more than 600 MW of renewable-powered capacity already online and a net-zero emissions goal by 2040, NTT is actively scaling AI-ready infrastructure globally.
4. CyrusOne Intelliscale™ (USA)
Modular data center campuses leveraging rear-door heat exchange and multiple liquid cooling setups, CyrusOne supports flexible scaling and consistent uptime. Its design is optimized to meet the demanding compute needs of AI workloads efficiently.
5. CoreSite Realty Corporation (USA)
Known for ultra-low latency and GPU-ready infrastructure, CoreSite supports AI-driven applications. Their data centers deliver direct-to-chip cooling and distributed connectivity essential for high-throughput inference workloads.
6. CoreWeave (US & Europe)
Operating 32 data centers and managing 250,000 GPUs as of early 2025, CoreWeave serves major clients including NVIDIA and OpenAI. Its flagship 450,000 sq ft supercomputer facility in Texas powers the fastest AI workloads in the world.
7. Cerebras Systems (US & Europe)
With six new data centers added in 2025, Cerebras offers inference capacity multiplying performance by over 20× and powers models like Llama API with speeds up to 2,500 tokens/sec and enhanced model throughput.
8. ABCI 3.0 (Japan)
Managed by Japan’s AIST, ABCI 3.0 uses 6,128 NVIDIA H200 GPUs to deliver over 6.22 exaflops of AI compute. Operational in early 2025, it supports generative AI and research workflows via MLOps and container-based access.
9. Isambard‑AI (UK)
Host to over 5,448 NVIDIA Grace‑Hopper GPUs, the UK’s energy-efficient modular data center delivers 21 exaflops of low‑precision performance and uses flash storage for AI workloads under 5 MW—expected to be fully operational by late 2024.
10. Stargate Norway (OpenAI / Aker / Nscale)
Announced in 2025, this gigafactory near Narvik will host 100,000 GPUs by 2026 and scale up to 520 MW power. Powered by hydropower and featuring closed-loop liquid cooling, it promises sovereign, efficient AI infrastructure for Northern Europe.
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