GPU deep learning training rack with NTS branded plaque
NTS Deep Learning Built in the USA

Deep Learning Training Infrastructure

Multi-GPU nodes with NVLink paths, dataset tiers, and kW validation for sustained NCCL loads—paired with APEX GPU catalogs when programs grow.
Deep Learning

Training and inference building blocks

NTS deep learning infrastructure spans multi-GPU training nodes, inference hosts, and dataset storage tiers designed alongside Cluster Solutions and APEX GPU programs.
Configurations include burn-in, NCCL soak, optional STIG imaging, and procurement support across federal and SLED vehicles so training and inference land on one integrator BOM.
Browse deep learning SKUs below or ask NTS to align GPU density, fabric, and dataset retention with your model factory roadmap.
NTS documents rack elevation, PDU draw, thermal headroom, and driver baselines on every RFQ so facility teams are not discovering constraints at install.
Related storage, networking, and software lines can ride the same quote when your vehicle and SOW allow—keeping multi-vendor programs under one accountable integrator.
Product categories

Explore our server platforms

Rackmount, GPU, blade, storage, cluster, high-density, and Ampere — engineered for scalability and efficiency.
NTS catalog

Available Deep Learning configurations

Select a platform below to configure, request a quote, or add to your procurement package.

Engineer-to-order — final BOM validated by NTS architects for workload, facility power, and contract vehicle.

  • Configure & quote
  • CPU / memory / storage specs
  • Contract-ready procurement
Specifications shown are reference configurations—final BOM validated by NTS architects for your workload, facility power, and security baseline.

Frequently asked questions

HBM capacity, host CPU/PCIe, east-west fabric, and checkpoint storage decide real throughput - NTS models those together.

  • Training vs inference differ
  • Frameworks matter

Follow software (CUDA vs ROCm), export posture, and second-source strategy - not peak TFLOPS alone.

  • Side-by-side BOMs
  • NTS maps both

Yes when in scope - engineering packages support fair opportunity and audit expectations.

  • CLIN structure
  • Fremont burn-in

GPU stress, interconnect rings, ECC scrub, firmware baselines, and thermal soak at representative airflow.

  • STIG imaging optional
  • Serial manifests