Next‑Gen AI Acceleration for LLM Training, Inference, HPC & Scientific Computing — Powered by the World’s Most Advanced AI GPU
- Provisioned in 10 minutes
- 20+ Tier‑1 global data centers
- Unmetered 1/10/25 Gbps bandwidth
- Crypto payments & 24/7 support included
NVIDIA H100 Tensor Core GPU Server Price
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🔍 Key Specifications
- Architecture: NVIDIA Hopper (TSMC 4N, 80B transistors)
- Memory: 80 GB HBM3 (SXM5) @ 3.35 TB/s; PCIe version uses HBM2e @ 2.0 TB/s
- Compute Performance (SXM5 / PCIe):
- FP64: 34 / 26 TFLOPS
- FP64 Tensor Core: 67 / 51 TFLOPS
- FP32: 67 / 51 TFLOPS
- TF32 Tensor Core: 989 / 756 TFLOPS
- FP16/BF16 Tensor Core: 1,979 / 1,513 TFLOPS
- FP64: 34 / 26 TFLOPS
- Form Factors & TDP:
- SXM5: dual-slot, 700 W TDP, NVLink 4.0 (900 GB/s).
- PCIe: dual-slot, 300–350 W TDP, PCIe Gen5 ×16, MIG support.
⚡ Why Choose H100?
Unmatched AI Training & Inference
Delivers up to 30× faster inference on large LLMs and 4× faster GPT-3 training vs A100.
Transformer Engine + DPX
First GPU with built-in Transformer Engine and DPX for 40× faster dynamic programming workloads.
Scalable Multi-GPU via NVLink/NVSwitch
SXM5 supports 900 GB/s NVLink with NVSwitch for building up to 8‑GPU pods.
Secure & Virtualized Ready
Enterprise security with Secure Boot and H100 NVL MIG support for up to 7 isolated tenants.
🎯 Ideal Use Cases
LLM Training & Inference at Scale
Efficient for 100B+ parameter models and massive inference workloads.
Scientific & HPC Workloads
Excels in molecular simulation, genomics, 3D FFT, and engineering tasks.
Transformer-based Analytics & Utilities
Speed up recommendation systems, graph analytics, and Tensor-heavy applications.
Multi-GPU Supercomputing Clusters
Build DGX or HGX-class systems delivering petaflop-scale compute.
Secure Multi-Tenant AI Services
Use MIG to host isolated AI workloads with guaranteed QoS and security.
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Deep Dive & FAQs
SX vs PCIe version, what’s best?
- SXM5 delivers peak compute, memory, and NVLink bandwidth; ideal for dense AI clusters.
- PCIe is easier to integrate into existing racks, with lower TDP and full software compatibility.
Is 700 W TDP manageable?
Yes, our data centers support high-density racks, with cooling and power to sustain peak TIFF workloads.
How well does multi-GPU scale?
With NVLink 4.0 and NVSwitch, H100 clusters massively scale compute and memory bandwidth across GPUs.
Does it support virtualization & multi-tenancy?
Yes, MIG enables up to 7 secure GPU instances per GPU, ideal for VDI or tenant-based AI services.
Which AI frameworks are supported?
Full stack compatibility: CUDA 12, cuDNN, TensorRT, HPC libraries, Triton Inference Server, PyTorch, TensorFlow.
Not sure exactly what you need?
No problem! Our talented engineers are here to help!
We will consult, architect, migrate, manage and do whatever it takes to help your business grow and succeed.
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