High Memory Capacity
The 80GB HBM2e memory ensures seamless handling of large models such as LLaMA 70B and beyond, supporting both training and inference.
Nvidia H100 GPU Hosting: High-Performance Deep Learning with 80GB HBM2e
The Nvidia H100 80GB HBM2e PCIe GPU is a cutting-edge solution designed for AI, deep learning, and large language model (LLM) workloads. Built on the Hopper architecture, it delivers exceptional performance for both training and inference, making it a key choice for developers and enterprises working on next-generation AI applications.
Specifications of Nvidia H100 80GB HBM2e PCIe
This specific configuration, with HBM2e memory and a PCIe interface, offers high compatibility for a variety of deep learning and HPC environments, particularly for developers seeking a PCIe-based solution.
Specifications
GPU Microarchitecture
Hopper
CUDA Cores
14,592
Memory
80GB HBM2e
Tensor Cores
456
Memory Bandwidth
2 TB/s
FP32 (float) performance
183 TFLOPS
FP64 (float) performance
67 TFLOPS
Interconnect
PCIe Gen5
Bus interface
PCIe 5.0 x16
Precision Support
FP64, FP32, FP16, BF16, INT8, INT4, FP8
Power Consumption
350 W maximum
Shading units
14,592
Texture mapping units
456
ROPs
24
Clock speeds
Base clock of 1095 MHz, boost clock of 1755 MHz, memory clock of 1593 MHz
Supported technologies
NVIDIA Hopper technology, NVIDIA Tensor Core GPU technology, Transformer Engine, NVLink switch system, NVIDIA Confidential Computing, 2nd Gen Multi Instance GPU (MIG), DPX instructions
The Nvidia H100 80GB HBM2e PCIe GPU for AI and HPC applications
The Nvidia H100 80GB HBM2e PCIe GPU is a game-changer for AI and HPC applications. Its massive memory capacity, advanced precision options, and Hopper architecture make it a top choice for large language model (LLM) training and inference. Paired with hosted solutions, it provides unparalleled scalability and flexibility for developers and enterprises alike.
If you're building the next breakthrough in AI, the H100 GPU offers the performance and reliability you need to stay ahead of the competition.
Why H100 80GB Is Ideal for Running LLMs
The Nvidia H100 80GB HBM2e stands out as an excellent choice for running LLMs due to:
Exceptional Performance
With up to 183 TFLOPS FP32 performance and advanced Tensor Cores, the H100 achieves unparalleled speed and efficiency for AI tasks.
FP8 Precision
Introduces 8-bit floating-point precision (FP8), enabling faster computations with reduced memory requirements, perfect for optimizing LLM workloads.
Compatibility and Scalability
The PCIe interface ensures compatibility with a wide range of systems, while the GPU can be scaled in clusters for even larger workloads.
H100 vs. Other GPUs
| GPU | Nvidia H100 | Nvidia A100 | Nvidia A40 | Nvidia RTX 4090 |
|---|---|---|---|---|
| Memory | 80GB HBM2e | 80GB HBM2 | 48GB GDDR6 | 24GB GDDR6X |
| Bandwidth | 2 TB/s | 1.55 TB/s | 696 GB/s | 1 TB/s |
| FP32 TFLOPS | 183 | 19.5 | 37.48 | 82.6 |
| Precision | FP64, FP32, FP8 | FP64, FP32, FP16 | FP32, FP16, INT8 | FP32, FP16, INT8 |
| Best Use Case | LLM training and inference | Large-scale AI training | Medium-sized LLMs and HPC | Consumer-grade AI and gaming |
Alternatives to H100 GPU Cards
Evaluate these alternatives if the H100 price or specs exceed your immediate needs.
The NVIDIA® GeForce RTX™ 4090 is the ultimate GeForce GPU. It brings an enormous leap in performance, efficiency, and AI-powered graphics.
The NVIDIA A100 Tensor Core GPU delivers unprecedented acceleration—at every scale—to power the world’s highest-performing elastic data centers for AI, data analytics, and HPC applications.
Nvidia V100 GPU cards are an ideal option for accelerating AI, high-performance computing (HPC), data science, and graphics. Find the right NVIDIA V100 GPU dedicated server for your workload.
FAQs of Dedicated H100 GPU Server Hosting
What is included in the H100 dedicated server hosting?
Our H100 dedicated server includes:
- Nvidia H100 GPU (80GB HBM2e)
- High-performance CPU and RAM for AI and HPC workloads
- SSD + NVMe storage for fast data processing
- 100Mbps - 1Gbps bandwidth for seamless connectivity
- Access to our U.S.-based data center
Where is the data center located?
Our servers are located in a U.S.-based data center, ensuring low latency and high-speed connectivity for North American clients.
Can I install custom software on the server?
Yes, you have full root access to the server, allowing you to install any software or tools you need for your project.
How do I monitor server performance?
You can monitor server performance using tools like nvidia-smi for GPU usage, as well as any additional monitoring software you choose to install.
Is the server scalable for larger workloads?
If your workload grows, we can help you scale by deploying additional servers or assisting with multi-GPU configurations.
What are the payment terms?
We offer monthly and yearly billing, allowing you to scale up or down based on your project requirements.
What are the main use cases for the H100 server?
Our H100 server is ideal for:
- Training and inference of large language models (LLMs) like GPT-4 and LLaMA
- Running deep learning frameworks such as TensorFlow, PyTorch, and JAX
- High-performance computing (HPC) for simulations, analytics, and more
Is the server shared or dedicated?
The H100 server is fully dedicated, meaning all resources (GPU, CPU, RAM, storage) are allocated exclusively to you.
What support is provided?
We provide 24/7 technical support for setup, troubleshooting, and server maintenance to ensure your operations run smoothly.
How does the H100 compare to other GPUs like A100 or A40?
The Nvidia H100 offers:
- Higher performance (183 TFLOPS FP32 vs. 19.5 TFLOPS for A100)
- Better memory bandwidth (2TB/s with HBM2e vs. 1.55TB/s for A100)
- Advanced FP8 precision for faster AI training and inference