Dedicated GPU Hosting
Single or multi-GPU environments hosted in our facilities, isolated exclusively for your workloads. Full control, zero noisy neighbours, enterprise-grade hardware.
GPU leasing, AI servers, GPU clusters, colocation, dedicated hosting, storage, memory, networking, and custom infrastructure — all from a single provider in Norway.
What We Offer
From a single dedicated GPU to a private multi-node cluster — we architect, deploy, and manage the compute environment your workloads demand.
Single or multi-GPU environments hosted in our facilities, isolated exclusively for your workloads. Full control, zero noisy neighbours, enterprise-grade hardware.
Fully isolated multi-GPU clusters with high-bandwidth NVLink and InfiniBand networking — designed for large-scale distributed AI training.
On-demand elastic GPU compute accessible via API — scale up for training runs, scale down during quiet periods. Pay for what you use.
Pre-configured software environments with CUDA, cuDNN, PyTorch, TensorFlow, and Kubernetes — ready from day one, maintained by our team.
Low-latency inference environments optimised for production AI deployment — with load balancing, auto-scaling, and 24/7 monitoring included.
Remote GPU-accelerated workstation access for AI developers, data scientists, and creative professionals requiring consistent high-performance compute.
Infrastructure
Archean Core AS purchases and owns all GPU hardware. You lease the compute — we carry the asset.
Continuous infrastructure monitoring with automated alerting, proactive maintenance, and rapid incident response.
Enterprise-grade power delivery and precision cooling systems designed for sustained GPU workloads at full TDP.
InfiniBand and high-speed Ethernet interconnects for low-latency, high-throughput cluster communication.
Backed by a service level agreement covering compute availability, with clear remedies for any downtime.
A dedicated technical support team available around the clock for infrastructure issues and configuration assistance.
We'll design a deployment around your specific workload and scale requirements.