The Flagship AI Training GPU
80GB HBM3 memory. 3.35 TB/s bandwidth. Transformer Engine for 4x faster LLM training. The H100 is the gold standard for training large language models.
Built for Large-Scale AI
The H100 accelerates every stage of the ML pipeline.
80GB HBM3 Memory
High-bandwidth memory delivers 3.35 TB/s bandwidth for training large language models and foundation models.
NVLink Interconnect
900 GB/s GPU-to-GPU bandwidth enables efficient multi-GPU training for models that don't fit on a single GPU.
Transformer Engine
Hardware-accelerated transformer computations with automatic mixed precision for faster training.
4x Faster Training
Up to 4x faster large language model training compared to A100, reducing time and cost.
Pre-configured Environment
PyTorch, TensorFlow, CUDA 12, and popular ML frameworks ready to use. Start training immediately.
Expert Support
Our ML infrastructure team helps with environment setup, optimization, and debugging.
Technical Specifications
H100 SXM specifications for reference.
| Specification | Value |
|---|---|
| GPU Memory | 80GB HBM3 |
| Memory Bandwidth | 3.35 TB/s |
| FP8 Performance | 3,958 TFLOPS |
| FP16 Performance | 1,979 TFLOPS |
| FP32 Performance | 989 TFLOPS |
| NVLink Bandwidth | 900 GB/s |
| TDP | 700W (SXM) |
| Form Factor | SXM5 / PCIe |
What H100 Excels At
Optimized for the most demanding AI workloads.
Large Language Model Training
Train GPT-style models, LLaMA, and other LLMs efficiently with H100's transformer engine and massive memory bandwidth.
LLM Fine-tuning
Fine-tune foundation models on your data. H100's memory capacity handles large batch sizes and long context lengths.
Distributed Training
Scale to multi-GPU and multi-node training with NVLink for efficient gradient synchronization.
High-Throughput Inference
Deploy large models for production inference with high throughput and low latency.
On-Demand & Reserved Pricing
Flexible pricing for every workload. Reserved instances available for long-term projects.
1x H100 SXM
- 1× NVIDIA H100 SXM
- 80GB HBM3
- 24 vCPU
- 240GB RAM
- 1TB NVMe
- Pre-configured ML Environment
4x H100 SXM
- 4× NVIDIA H100 SXM
- 320GB HBM3
- 96 vCPU
- 960GB RAM
- 4TB NVMe
- Pre-configured ML Environment
8x H100 SXM
- 8× NVIDIA H100 SXM
- 640GB HBM3
- 192 vCPU
- 1.9TB RAM
- 8TB NVMe
- Pre-configured ML Environment
Need a custom configuration or cluster? Contact us for a quote.
Frequently Asked Questions
What's the difference between H100 SXM and PCIe?
H100 SXM has higher power (700W vs 350W) and NVLink support for multi-GPU configurations. SXM offers better performance for large-scale training. PCIe is suitable for single-GPU workloads and inference.
How does H100 compare to A100 for training?
H100 offers up to 4x faster training for large language models thanks to the Transformer Engine, higher memory bandwidth (3.35 TB/s vs 2 TB/s), and improved FP8 support. For LLM workloads, H100 provides significantly better performance per dollar.
What frameworks are pre-installed?
PyTorch 2.x, TensorFlow 2.x, CUDA 12.x, cuDNN, NCCL, and Hugging Face Transformers are pre-installed. We also provide Docker images with popular ML frameworks.
Can I use H100 for inference?
Absolutely. H100 excels at high-throughput inference, especially for large language models. The Transformer Engine accelerates both training and inference workloads.
Is reserved pricing available?
Yes. Reserved instances (1-month, 3-month, annual) offer 20-40% discounts compared to on-demand pricing. Contact our team for a quote.
Get Your H100 Instance Today
Talk to our team about your AI workload. We'll help you configure the right setup.