GPU compute

Large-scale sovereign GPU deployments.

deployment options

GPU fleets, custom-architected at industrial scale.

OneQode designs, deploys and operates multi-megawatt GPU fleets for the world's largest AI programmes – built around your workload, delivered on the stack you run, operated alongside your team.

Architected to your programme.

Custom-built at your scale.

Multi-MW fleets specified end-to-end: GPU, topology, storage, power and cooling engineered for the workload you're running – training, inference, or HPC.

Delivered however you operate.

Bare metal, Kubernetes, or co-designed.

Take the fleet as raw bare metal, drive it through Kubernetes and APIs, or have us co-engineer a deeper integration with your platform team.

Run as a partnership.

Joint operations, not a handover.

Engineering and ops working alongside yours from design through 24/7 run-state. We carry the fleet with you, not over a wall.

GPU fleet deployment locations | | infrastructure| gpu compute
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GPUs where it matters

Deploy GPU fleets where latency, sovereignty, and growth matter.

Multi-MW capacity placed where workloads and data live.

Reserve capacity
What we deliver

OneQode brings together supply, topology, network, sovereignty, and operations into one deployable compute platform.

  • Large-scale clusters

    Multi-MW GPU clusters designed and deployed to customer specifications.

  • Fleet control via bare metal or k8s

    Handed over exactly how you need it for ease of operation.

  • Workload-matched topology

    Cluster topology and internal fabric shaped to the workload.

  • Customisable network delivery

    Our own private global backbone, with deep interconnections to eyeball networks.

  • Sovereign deployment options

    Defined boundaries, security, key management, and audit options.

  • Monitoring and support

    24/7 engineering operations to ensure a smooth running fleet.

Sovereign GPU region infrastructure | | infrastructure| gpu compute
See our latest deployments
Sovereign by construction

Sovereign regions, designed with you and operated together.

Defined network boundaries, customer-held keys, jurisdiction-aware operations – engineered alongside your team and run jointly. Joint Venture options available.

Reserve capacity
  • 7+ Yrs

    Operating critical infrastructure

  • 4/10

    Top quant firms as customers

  • 24/7

    NOC and ops coverage

  • 13+

    countries with active infrastructure

where we operate

GPU clusters, deployed where the programme needs them.

Three deployment shapes that come in alone, or combined within one fleet.

Reserve capacity
  • One operating model across all three
  • Custom-architected to the workload
  • Mix and match within one programme

Multi-node GPU clusters

Multi-MW GPU clusters on private fabric.

Private or sovereign region

Region-scoped capacity with sovereign access posture.

Vanguard modular datacenter

On-site pods for federal, defence, oil and gas, and edge.

specifications

Architected end to end – accelerator, fabric, storage, network, observability, delivery.

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Cluster scale
Multi-MW Multi-megawatt deployments, thousands to tens of thousands of accelerators.
GPU platform
AMD Instinct Partnered with AMD to deploy the Instinct family at frontier scale, including the next-generation Helios platform.
Internal fabric
High-bandwidth, low-latency Topology and fabric chosen per programme - sized to the workload.
Storage
Storage built for the workload Parallel filesystems at NVMe line rate, tiered enterprise storage with WEKA and VAST Data, or custom architectures designed by our storage engineers - built for the need.
Network
Performance global backbone OneQode's carrier network is a private highway for traffic. Optimized and customizable to your requirements, from subsea to routing and interconnections.
Observability
Integrated with your stack Real-time telemetry from every layer of the fleet, streamed into your monitoring stack and operated jointly with your SRE team.
Delivery model
Co-engineered delivery Hand over as bare metal, drive via Kubernetes and APIs, or have our engineering team co-build a deeper integration with your platform.
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use cases
Deploy GPU capacity where the workload needs to run.
  • AI

    Private GPU capacity for frontier workloads.

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  • finance

    Low-latency infrastructure for performance systems.

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  • enterprise

    In-house AI that stays within your organization.

    View case
  • media & entertainment

    GPU infrastructure for real-time media pipelines.

    View case
  • government

    Sovereign compute for public-sector infrastructure.

    View case

Ready to get started?

Talk to our infrastructure team about your next deployment.