NVIDIA HGX H100 4-GPU

baseboard
4× H100
NVLink
2022
FP64
0.1
PFLOPS
FP32
0.3
PFLOPS
Power
4.2
kW Total
Memory
320
GB Total

HGX H100 4-GPU configuration for smaller deployments

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FP64
0.14
PFLOPS
32.4 TFLOPS/kW
FP32
0.27
PFLOPS
63.8 TFLOPS/kW
TF32
1.98
PFLOPS
941.9 TFLOPS/kW
FP16
3.96
PFLOPS
1884.8 TFLOPS/kW

System Details

GPU Configuration

GPU Count: 4 GPUs
Architecture: Hopper
Interconnect: NVLink

System Specifications

Form Factor: baseboard
Total Power: 4.2 kW
Total Memory: 320 GB
Memory Bandwidth: 13.4 TB/s

Precision Performance Breakdown

PrecisionSystem PerformancePer GPUEfficiency
0.136 PFLOPS 34.0 TFLOPS 32.4 TFLOPS/kW
0.268 PFLOPS 67.0 TFLOPS 63.8 TFLOPS/kW
1.978 PFLOPS 494.5 TFLOPS 941.9 TFLOPS/kW
3.958 PFLOPS 989.5 TFLOPS 1884.8 TFLOPS/kW
3.958 PFLOPS 989.5 TFLOPS 1884.8 TFLOPS/kW
7.916 PFLOPS 1979.0 TFLOPS 3769.5 TFLOPS/kW
7.916 PFLOPS 1979.0 TFLOPS 3769.5 TFLOPS/kW

Where a vendor states a basis, the figure shown is the dense one, and any figure it publishes is listed separately. Vendors commonly headline the sparse number instead: for NVIDIA's 2:4 structured sparsity that is exactly twice the dense figure, though other vendors' sparse modes do not all follow that ratio.

Powered by NVIDIA H100

This system utilizes 4 × 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

Flopper Spec Sheet

NVIDIA HGX H100 4-GPU specifications, generated from our database. Printable.

Vendor product page

NVIDIA HGX H100 4-GPU documentation

View ↗

workstation-datasheet-dgx-spark-gtc25-spring-nvidia-us-3716899-web.pdf

NVIDIA • 2025-10-16

View Document ↗

NVIDIA DGX Documentation

System guides, deployment resources

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Typical Use Cases

Large Language Model Training
Distributed Deep Learning
Multi-GPU Inference
HPC Simulations
Scientific Computing

The NVIDIA HGX H100 4-GPU runs 4× H100 GPUs over NVLink, delivering 7.92 PFLOPS FP8 dense.