AI & GPU Colocation in Phoenix: High-Density Data Centers for Machine Learning | Arizona Colocation
AI & HPC 8 min read

AI & GPU Colocation in Phoenix: High-Density Data Centers for Machine Learning

Find the best data centers in Phoenix for AI training and GPU workloads. Compare high-density power, liquid cooling, and GPU-ready colocation facilities in Arizona.

The Rise of AI Colocation Demand in Arizona

The explosive growth of artificial intelligence has created massive demand for high-density colocation capable of supporting GPU clusters. Arizona's Phoenix metro area has emerged as a prime location for AI workloads, with several purpose-built facilities offering the power density, cooling, and connectivity these deployments require.

What Makes AI Colocation Different?

Traditional colocation provides 5-10 kW per rack. AI and GPU workloads can demand 30-100+ kW per rack, requiring fundamentally different infrastructure:

  • High-density power delivery - 30 kW to 100+ kW per rack vs standard 5-10 kW
  • Advanced cooling - Liquid cooling (direct-to-chip or immersion) for GPU heat loads
  • Low-latency networking - 100 Gbps+ interconnects for distributed training
  • Massive power capacity - AI campuses need 50-240+ MW total

Top Phoenix-Area Facilities for AI Workloads

NTT DATA - Mesa (240MW)

The largest AI-ready campus in Arizona with 240MW of planned capacity. Purpose-built with liquid cooling capabilities for GPU workloads. Backed by NTT Group's $100B+ revenue and global Tier 1 network backbone.

EdgeCore Digital - Mesa

High-density hyperscale facility designed for AI and cloud workloads. Supports 30+ kW per rack with future liquid cooling integration.

Aligned Data Centers - Phoenix

Patented Delta3 cooling technology enables efficient high-density deployments up to 32MW per customer. Industry-leading PUE below 1.2.

Why Arizona for AI Colocation?

  • Abundant power - Ample utility capacity with multiple substations
  • Cheap electricity - $0.06-0.08/kWh vs $0.15+ in California (saves millions at scale)
  • Natural cooling advantage - Dry climate enables free cooling 8+ months/year
  • Low latency to West Coast - < 8ms to Los Angeles for inference workloads
  • Solar energy access - Renewable energy options for ESG-conscious AI companies

Cost Comparison

  • Per kW/month: $100-150 in Arizona vs $150-200+ in California
  • 1MW deployment: $100K-150K/month in Arizona vs $150K-200K in Silicon Valley
  • Power savings: 30-50% lower electricity costs than California
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