NVIDIA H100 PCIe — AI Training & Inference GPU
The NVIDIA H100 PCIe GPU delivers industry-leading performance for large language models, multi-modal AI, and high-performance computing. Designed on NVIDIA’s Hopper architecture, it provides unmatched acceleration and efficiency for both training and inference workloads.
80GB HBM3 Memory
Massive Throughput for Deep Learning
PCIe Gen5 Connectivity
Industry Standard for Foundation Models
GPU Specifications
Detailed technical specifications of the NVIDIA H100 PCIe GPU designed for advanced AI training, inference, and high-performance computing.
| Feature | Details |
|---|---|
| Architecture | NVIDIA Hopper |
| Memory | 80GB HBM3 |
| Memory Bandwidth | 3.35 TB/s |
| Tensor Cores | 4th Gen |
| Interconnect | PCIe Gen5 |
Ideal Use Cases
NVIDIA H100 PCIe GPUs accelerate demanding AI workloads and high-performance computing tasks across research, enterprise, and advanced analytics environments.
Large Language Model (LLM) Training
Transfer Learning & Fine-Tuning
AI Research Workflows
Scientific Simulation & Analytics
Why Choose H100 on Fluidcore
Deploy H100 clusters on a platform built for AI — with bare-metal performance, high-speed networking, and sovereign infrastructure. Our platform delivers GPU performance without hypervisor overhead and supports rapid scaling for enterprise workloads.
Bare-Metal Performance
Run NVIDIA H100 GPUs directly on bare-metal infrastructure without hypervisor overhead, ensuring maximum compute efficiency.
High-Speed Networking
Optimized networking architecture designed for distributed AI training and ultra-fast data transfer across GPU clusters.
Rapid Scaling
Scale GPU clusters instantly to handle enterprise AI workloads, from experimentation to production-scale deployments.
Sovereign Infrastructure
Maintain full control over data and compute resources with secure, sovereign infrastructure built for enterprise AI.
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View Details →Ready to Deploy NVIDIA H100?
Launch high-performance AI workloads with NVIDIA H100 GPUs on Fluidcore’s enterprise-grade infrastructure designed for large-scale machine learning and advanced compute.