Multi-node GPUs. Built to scale.
Dedicated clusters for distributed training, fine-tuning and inference. We find the capacity, check the provider and negotiate the terms, so you receive one deployment instead of a pile of nodes.
Built for distributed AI workloads.
Compute, fabric and support arrive as one deployment, from providers deploying NVIDIA HGX and GB300 NVL72 platforms.
High-speed interconnect
Non-blocking InfiniBand or RoCE between nodes, sized to your job.
NVLink and NVSwitch
Fast GPU-to-GPU links inside each system, on supported NVIDIA platforms.
Dedicated capacity
Reserved infrastructure for your team, not a shared pool.
We stay involved
From signature to the first training run, with one point of contact.
One fabric. Three demanding workloads.
Frontier training
Scale training across many nodes with a fabric built for it.
Fine-tuning
Sustained fine-tuning and post-training on reserved GPUs.
Inference
Production capacity for high-throughput, latency-sensitive serving.
What we check before we introduce a provider.
- Hardware. GPU model, node configuration and delivery schedule, confirmed in writing.
- Power. Contracted power, redundancy and the timeline to energize.
- Network. Interconnect, uplinks and the provider's fabric design.
- Track record. Previous deployments, uptime history and references.
- Service terms. Uptime commitments, support and remedies in the SLA.
- Company. Ownership, financial standing and who signs the contract.
Need multi-node GPU capacity?
Tell us the GPU type, cluster size, region and start date. We reply within one business day.
Request capacity