Use Case

Train frontier models without sharing the fabric

Multi-node clusters reserved for you alone, with the interconnect distributed training actually needs. No preemption, no spot evictions, nobody else's all-reduce in your fabric.

AI Model Training
800 Gb/s
Per-GPU fabric
0
Spot evictions
100%
Dedicated hardware
Capabilities

Built in, not bolted on

01

Multi-node NVLink fabric

Non-blocking XDR InfiniBand at up to 800 Gb/s per GPU, with NVLink inside the rack. Gradients keep moving across thousands of GPUs at near-linear scaling efficiency.

02

Reproducible runs

Dedicated hardware means deterministic performance. Your training curves look the same on run one and run one hundred.

03

Checkpoint-grade storage

DDN EXAScaler parallel storage with GPUDirect. Checkpoints write fast and restore faster, so a failed run costs you minutes, not a day of GPU hours.

04

Reserved capacity

Your GPUs are yours for the whole campaign, with hot spares standing by, so a failed node or a firmware update never stalls the run.

Recommended hardware
GB300 NVL72GB200 NVL72
All GPUs

Other solutions

08Get started

Done sharing
someone else's
GPUs?

Tell us what you're building. We'll scope the cluster, quote a fixed monthly number, and commit to a commissioning date in writing. Dedicated capacity takes a quarter or more to stand up. The difference with us is that you'll know exactly when yours arrives.

  • A cluster proposal scoped to your workload
  • One fixed monthly price, no egress or metering
  • A direct line to the engineers who racked it

Request a proposal

No commitment. Reply within one business day.