New cluster increases available GPU capacity for enterprises running large-scale AI inference applications
DeepInfra, a purpose-built cloud platform for high-throughput AI inference, today announced the opening of a new data center location in Toronto.
Global AI infrastructure demand is increasingly being driven by inference workloads as enterprises shift from model training to production-scale deployment. According to research from McKinsey & Company, AI inference is projected to account for more than 40% of total data center demand by 2030, growing at an estimated ~35% compound annual growth rate as real-time applications, agentic systems, and high-volume API traffic continue to scale. This shift is placing sustained pressure on GPU availability and accelerating the need for distributed, high-density compute clusters optimized for low-latency inference.
The new 1.7 MW facility marks DeepInfra’s ninth data center location and its first outside the United States. It will host over 1,000 NVIDIA Blackwell B300 GPUs, significantly expanding the company’s global inference capacity. The deployment strengthens DeepInfra’s infrastructure strategy, enhancing its ability to deliver low-latency, cost-efficient AI inference services across North American and international markets.
“Enterprises are moving from experimentation to production at unprecedented speed, and that shift demands infrastructure that is both scalable and globally distributed,” said Nikola Borisov, CEO and co-founder of DeepInfra. “This Toronto cluster is a foundational step in expanding our capacity beyond the U.S. and ensuring customers can run AI workloads closer to where their users and data reside.”
The Toronto facility closely follows DeepInfra’s Series B investment and is part of its ongoing investment strategy to expand inference capacity across strategically positioned regions, with additional international deployments under evaluation as demand for GPU-intensive workloads continues to grow.
To learn more, visit deepinfra.com.
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