INFRASTRUCTURE
Enterprise-Grade GPU Infrastructure
Dedicated NVIDIA HGX clusters with high-performance networking for large-scale AI training and inference
GPU PLATFORMS
Supported NVIDIA GPU Platforms
A comprehensive portfolio of NVIDIA data center GPUs to meet different performance, memory, and cost requirements.
| GPU | Architecture | Memory | Peak Compute | Deployment | Target Use |
|---|---|---|---|---|---|
| B300 | Blackwell Ultra | ~288GB HBM3e | ~9–10 PFLOPS (FP8) | HGX B300 (8 GPUs) | Ultra-scale LLM training |
| B200 | Blackwell | ~192GB HBM3e | ~8 PFLOPS (FP8) | HGX B200 (8 GPUs) | Enterprise AI training |
| H200 | Hopper | ~141GB HBM3e | ~4 PFLOPS (FP8) | HGX H200 (8 GPUs) | Memory-intensive AI & HPC |
| H100 | Hopper | 80GB HBM3 | ~4 PFLOPS (FP8) | HGX H100 (8 GPUs) | General AI & HPC |
| A100 | Ampere | 40GB / 80GB HBM2e | ~312 TFLOPS (FP16) | HGX A100 (8 GPUs) | Cost-efficient AI workloads |
ARCHITECTURE
HGX Architecture & InfiniBand Networking
All GPU clusters are built on NVIDIA HGX reference architecture, ensuring optimal GPU-to-GPU communication, system stability, and scalability.
- Ultra-low latency GPU communication
- High bandwidth for distributed training
- Reliable performance for mission-critical AI workloads
Designed for large-scale LLM training, multi-node inference, and HPC applications that require deterministic performance.
SPECIFICATIONS
Technical Specifications
Enterprise-grade hardware and infrastructure
GPU Hardware
- H100
- H200
- B200
- B300
Network Connectivity
- 400G/800G InfiniBand
- 10Gbps Direct
- < 5ms Latency
- Dedicated Fabric
Storage Systems
- NVMe 8TB
- S3 Compatible
- 1M+ IOPS
- Zero Egress Fees
Need a Custom Quote?
Contact our enterprise team for dedicated infrastructure proposals