GPU-Dense Compute
Configurations range from single A100 nodes to eight-GPU H200 platforms, enabling customers to match infrastructure cost and capacity to workload scale.
INFRASTRUCTURE
The GPU is only one layer of performance.
AI workloads depend on the complete system: accelerator memory, host CPU and RAM, storage throughput, network capacity, power, cooling, and reliable operations. TREXVEX configurations are structured around that full infrastructure stack.
Enterprise NVMe
High-throughput local NVMe capacity supports checkpoints, datasets, model artifacts, temporary training data, and I/O-heavy inference workflows.
High-Speed Networking
10 Gbps, 25 Gbps, and 100 Gbps connectivity options are aligned with increasingly data-intensive and distributed accelerator workloads.
High-Memory Hosts
Large ECC memory allocations reduce host-side bottlenecks for preprocessing, model loading, data pipelines, and multi-process AI applications.
Dedicated Allocation
Product configurations are positioned as dedicated compute allocations, supporting more predictable performance for sustained production and research workloads.
Operational Workflow
Orders, invoices, payment submission, and billing history are tracked through the client area to provide a clear commercial record for each deployment.