GPU Clusters
Custom GPU Clusters Powered by NVIDIA
Deploy multi-node NVIDIA GPU clusters built for
training—custom hardware, custom contract.
Massed Compute Clusters are ideal for large-scale model training, simulations, and other compute-heavy workloads that demand serious power. Whether you’re training an LLM or running a short-term, high-intensity AI project, clusters are tailored to meet your workload head-on.
We build custom multi-node clusters using our in-stock inventory of NVIDIA GPUs—including H100 SXM, A100 SXM, and A100 DGX. Each server includes 8 GPUs, pre-connected with high-speed Infiniband and ready to run. You choose the specs. We deploy it—typically within one business day. Submit your specs using our self-serve form to get started.
Full control, front to back. Choose your GPU type, node count, deployment window, and pricing model based on the exact needs of your workload. Whether you’re training for a week or scaling up for a month, you only pay for what you need—no long-term lock-ins, no overages, no wasted spend.
We own the hardware. We run the setup. No third-party platforms. No delays. You’ll get direct access to the engineers who built your cluster and a dedicated Slack channel for real-time support.
18x nodes with 2x “Bianca” GB200 Superchips, each with
– 2 Blackwell GPUs 384 GB HBM3e (total of 72x)
– 1 Grace CPU with 72 Arm Neoverse V2 cores (total of 36x)
– 14.4 Tbps Infiniband
– Up to 3PB high-performance converged storage
18x nodes with 2x “Bianca” GB200 Superchips, each with
– 2 Blackwell GPUs 384 GB HBM3e (total of 72x)
– 1 Grace CPU with 72 Arm Neoverse V2 cores (total of 36x)
– 14.4 Tbps Infiniband
– Up to 3PB high-performance converged storage
18x nodes with 2x “Bianca” GB200 Superchips, each with
– 2 Blackwell GPUs 384 GB HBM3e (total of 72x)
– 1 Grace CPU with 72 Arm Neoverse V2 cores (total of 36x)
– 14.4 Tbps Infiniband
– Up to 3PB high-performance converged storage
Massed Compute is an NVIDIA Preferred Partner, giving you access to the highest-performing solutions in GPU technology. Train a machine learning model, run simulations, or analyze big data with the confidence that every instance will run effectively.
GPUs on-demand, at scale.