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Instant access to NVIDIA H100 PCIe GPUs—ideal for AI model training and big data processing—with hourly pricing, global availability, and fast deployment. Experience the power of NVIDIA's Hopper architecture with features like the Transformer Engine and fourth-generation Tensor Cores for up to 4x faster training of large language models. Rent on the Runpod platform to enjoy flexible, cost-effective cloud GPU rentals with no capital investment and seamless scalability.
Why Choose NVIDIA H100 PCIe
The NVIDIA H100 PCIe GPU is among the best GPUs for AI, offering exceptional computational power for AI workloads, combining top-tier performance with cost-efficient rental options. It empowers organizations of all sizes to leverage enterprise-grade computing without significant capital investment, fueling innovation in AI and data processing.
Benefits
- Unmatched AI and ML Performance
Powered by NVIDIA's Hopper architecture, the H100 PCIe features advanced Transformer Engines and fourth-generation Tensor Cores, delivering up to 4x faster training for large language models and generative AI tasks compared to previous generations like the A100. These significant differences between A100 and H100 make the H100 an optimal choice for demanding AI workloads. For information on the best LLMs on Runpod, refer to our FAQ. - Cost-Efficiency Through Flexible Rentals
By renting H100 PCIe GPUs, organizations can avoid the substantial upfront cost of purchasing NVIDIA H100 hardware outright. Renting lets you pay only for the compute time you use, making it accessible for startups and research teams alike. For current rates, see the Runpod pricing page. - Scalability and Operational Flexibility
Renting GPUs from platforms like Runpod allows for immediate provisioning and resource scalability, including options like serverless GPU endpoints, enabling teams to adjust their computing power based on project demands without dealing with hardware maintenance and exploring various serverless GPU platforms.
For a detailed comparison between the H100 NVL and H100 PCIe, see H100 NVL vs H100 PCIe.
Specifications
| Feature | Value |
|---|---|
| Architecture | NVIDIA Hopper (GH100) |
| Manufacturing Process | 5nm TSMC |
| Transistors | 80 billion |
| Die Size | 814 mm² |
| Form Factor | Full-height, full-length (FHFL), dual-slot PCIe card |
| PCIe Interface | PCI Express 5.0 x16 (supports Gen5 x8 and Gen4 x16) |
| NVLink Support | Up to 3 bridges, 600 GB/s max NVLink bandwidth |
| GPU Memory | 80 GB HBM2e |
| Memory Bandwidth | 2 TB/s |
| Clock Speeds | Base 1,095 MHz, Boost 1,755 MHz |
| Power Consumption | 350 W (via 1× 16-pin power connector) |
| Multi-Instance GPU (MIG) | Supported (up to 7 instances) |
| Security | Secure Boot (CEC) supported |
| Weight | Approximately 1,200g |
| Display Output | None – designed purely as a compute accelerator |
| FP64 Performance | 26 TFLOPS |
| FP64 Tensor Core Performance | 51 TFLOPS |
| FP32 Performance | 51 TFLOPS |
| TF32 Tensor Core Performance | 756 TFLOPS* |
| BFLOAT16 Tensor Core Performance | 1,513 TFLOPS* |
| FP16 Tensor Core Performance | 1,513 TFLOPS* |
| FP8 Tensor Core Performance | 3,026 TFLOPS* |
| INT8 Tensor Core Performance | 3,026 TOPS* |
For detailed information on the performance of the H100 GPU, refer to our comprehensive FAQ.
FAQ
What are the typical hourly rental rates for NVIDIA H100 PCIe GPUs?
Rental rates for H100 PCIe GPUs vary by provider and instance type (on-demand vs. reserved, Community Cloud vs. Secure Cloud). For current Runpod rates, refer to the Runpod pricing page.
What factors influence the pricing of NVIDIA H100 PCIe GPU rentals?
Several factors influence pricing, including whether the instance is on-demand or reserved, the choice between Community or Secure Cloud environments, and any provider-specific discounts or promotions. Additionally, data transfer, storage, and additional services also affect the total cost. For detailed pricing information, refer to the Runpod pricing page.
What should you consider when choosing a GPU rental provider?
When choosing a GPU rental provider, consider performance and reliability (with consistent performance data and uptime guarantees), scalability (the provider's ability to grow with your needs), global availability (to minimize latency for distributed teams), support quality (24/7 customer support, comprehensive documentation, and active user communities), and integration and compatibility (pre-configured environments with popular AI frameworks to minimize setup time).
How can you get started with H100 PCIe rentals effectively?
To get started with H100 PCIe rentals effectively, assess your workload to determine computational requirements, set up your environment using containerized instances with pre-configured environments, optimize for cost-efficiency by utilizing spot instances or reserved pricing, leverage provider tools for management and deployment, and monitor usage to avoid over-provisioning and identify optimization opportunities.
What security considerations should be addressed for sensitive workloads on rented H100 PCIe GPUs?
For sensitive workloads on rented H100 PCIe GPUs, address security concerns by ensuring data encryption at rest and in transit, confirming compliance certifications (such as GDPR, HIPAA, SOC 2), understanding resource isolation in shared environments, ensuring robust user authentication and authorization features, and confirming the provider can accommodate any geographic requirements for data storage. For more on this, see Runpod security.
