CONCRETE ENGINE CAPACITY
Dedicated NVIDIA and AMD GPU infrastructure for training, inference and private AI. Choose a managed cluster, bare-metal access or bring your own GPUs.
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Bring Your Own GPUs
Select a reference configuration. Final hardware availability, capacity and delivery schedule are confirmed during technical and commercial qualification.
Typical deployment: 3–6 months. Deployment schedules depend on site readiness, power availability, equipment lead times, technical qualification and commercial agreement.
NVIDIA GB300 NVL72
Rack-scale Blackwell Ultra infrastructure for large training and inference workloads.
72 Blackwell Ultra GPUs · NVLink rack-scale architecture · Direct-to-chip liquid cooling · Managed or bare metal · Multi-rack deployments
NVIDIA HGX B300
Dedicated eight-GPU systems for training, inference and enterprise AI.
8 Blackwell Ultra GPUs per node · High-speed NVLink · Air- or liquid-cooled options · Managed or bare metal · Multi-node clusters
NVIDIA H200
Proven GPU infrastructure for inference, fine-tuning and research workloads.
8-GPU node configurations · Dedicated infrastructure · High-speed networking · Managed or bare metal · Flexible cluster sizes
AMD Instinct
AMD GPU infrastructure supported by Concrete Engine’s GPU-agnostic platform.
ROCm-compatible environment · Dedicated infrastructure · Workload-specific configurations · Managed or bare metal · Private deployment options
We integrate qualified customer-owned systems with the facility, power, cooling, network integration and ongoing operations required for your workload.
Tell us what you need. Our infrastructure team will review capacity, qualification and next steps.
PLAN YOUR DEPLOYMENT
Plan Your Deployment
Reserve dedicated capacity, deploy your existing GPUs or discuss a sovereign environment.
