NVIDIA DGX H100
rack
8× H100
NVSwitch + NVLink
2022
FP64
0.3
PFLOPS
FP32
0.5
PFLOPS
Power
8.5
kW Total
Memory
640
GB Total
Enterprise AI system with 8x H100 SXM5 GPUs
FP64
0.27
PFLOPS
32.0 TFLOPS/kW
FP32
0.54
PFLOPS
63.1 TFLOPS/kW
TF32
3.96
PFLOPS
930.8 TFLOPS/kW
FP16
7.92
PFLOPS
1862.6 TFLOPS/kW
System Details
GPU Configuration
GPU Model: NVIDIA
H100
SXM5 80GB
GPU Count: 8 GPUs
Architecture: Hopper
Interconnect: NVSwitch + NVLink
System Specifications
Form Factor: rack
Total Power: 8.5 kW
Total Memory: 640 GB
Memory Bandwidth: 26800 GB/s
Precision Performance Breakdown
| Precision | System Performance | Per GPU | Efficiency |
|---|---|---|---|
| FP64 | 0.272 PFLOPS | 34.0 TFLOPS | 32.0 TFLOPS/kW |
| FP32 | 0.536 PFLOPS | 67.0 TFLOPS | 63.1 TFLOPS/kW |
| TF32 | 3.956 PFLOPS | 494.5 TFLOPS | 930.8 TFLOPS/kW |
| FP16 | 7.916 PFLOPS | 989.5 TFLOPS | 1862.6 TFLOPS/kW |
| BF16 | 7.916 PFLOPS | 989.5 TFLOPS | 1862.6 TFLOPS/kW |
| FP8 | 15.832 PFLOPS | 1979.0 TFLOPS | 3725.2 TFLOPS/kW |
| INT8 | 15.832 PFLOPS | 1979.0 TFLOPS | 3725.2 TFLOPS/kW |
Powered by NVIDIA H100
This system utilizes 8 × NVIDIA H100 SXM5 80GB GPUs, each delivering exceptional performance for AI and HPC workloads.
Per GPU TDP
700W
Per GPU Memory
80 GB
Process Node
4nm
Architecture
Hopper
Documentation & Resources
workstation-datasheet-dgx-spark-gtc25-spring-nvidia-us-3716899-web.pdf
NVIDIA • 2025-10-16
NVIDIA DGX Documentation
System guides, deployment resources
Typical Use Cases
Large Language Model Training
Distributed Deep Learning
Multi-GPU Inference
HPC Simulations
Scientific Computing
The NVIDIA DGX H100 with 8× H100 GPUs is designed for enterprise-scale workloads requiring 0.3 PFLOPS of compute power with NVSwitch + NVLink interconnect for efficient multi-GPU communication.