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H200 on AWS: Pricing, Specs & How to Rent

Deploybase · October 12, 2025 · GPU Pricing

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H200 on AWS: Pricing Breakdown

AWS H200 pricing exceeds $3/hr depending on region. Available through EC2 p5e instances but supply is tight.

Compare: RunPod is $3.59/hr, Lambda H200 pricing requires contacting sales, CoreWeave clusters are $50.44/hr (8xH200).

Reserved instances save 30-40% over 1-year commitments. Spot instances are cheaper but preemptable. On-demand has no commitment but higher hourly rates.

Separate charges: EBS storage ($0.10-0.125/GB-month), data egress ($0.02/GB). Model uploads add up fast.

H200 GPU Specifications

The NVIDIA H200 represents the latest generation of data center tensor accelerators. It features 141 GB of HBM3e memory, 76% more than the H100's 80GB. This expanded memory enables larger batch sizes and longer sequence lengths in transformer models. The H200 delivers the same compute throughput as the H100 SXM (67 TFLOPS FP32, 989 TFLOPS TF32); the primary advantage is memory capacity and bandwidth.

Memory bandwidth reaches 4.8 TB/s, a significant improvement over the H100's 3.35 TB/s. This speed matters enormously for transformer inference, where memory throughput often limits performance. The H200 can serve larger models at higher throughput without bottlenecks inherent in smaller GPUs.

Sparsity acceleration features in H200 GPUs skip computations on zero values, reducing effective workload on sparse models. Transformers with structured sparsity see dramatic speedups. The GPU supports 50 teraflops of structured sparsity operations, effectively multiplying throughput for compatible workloads.

TensorRT-LLM and other inference libraries have begun optimizing specifically for H200's architectural advantages. Teams deploying inference workloads benefit from these software optimizations. Training workloads enjoy the expanded memory but may not utilize sparsity features as effectively.

Power consumption peaks at approximately 700W, comparable to the H100 SXM. Cooling requirements scale accordingly, requiring reliable data center infrastructure. The H200's added memory and bandwidth come with only modest power increases relative to throughput gains, improving efficiency metrics.

How to Rent H200 on AWS

Getting H200s from AWS requires navigating EC2's instance catalog. The p5e.48xlarge instance type includes H200-equipped options. Users select their desired region, checking availability beforehand since H200 access varies by location. AWS regions in us-east-1, us-west-2, and eu-west-1 typically have H200 availability.

Creating an EC2 instance begins with the AWS Management Console. Users choose the AMI, specifying whether to use a standard Linux image or pre-configured deep learning AMI. AWS provides CUDA-pre-installed environments, reducing setup time. Custom AMIs allow teams to version control their software stack.

Instance configuration requires selecting security groups, VPC settings, and storage. EBS volumes attach automatically with the instance, providing persistent storage between shutdowns. Users configure volume size based on model checkpoints and datasets. Larger volumes add proportional storage costs.

SSH key pairs enable command-line access. Users can upload files via scp or S3 integration. AWS Systems Manager Session Manager offers browser-based SSH without key management overhead. Jupyter notebooks can run directly on instances for interactive development.

Monitoring tools track instance metrics including CPU, GPU utilization, and memory usage. CloudWatch alerts notify users of resource constraints. AWS Glue allows job scheduling for batch training runs. Lambda functions can trigger instance creation and termination automatically based on workload timing.

Terminating instances stops charges immediately. EBS volumes persist after instance termination unless explicitly deleted. Reserved capacity from reserved instances remains chargeable even if instances stop running, so reservation strategies require careful planning.

AWS H200 vs Other Providers

AWS H200 pricing sits above most competitors due to EC2's margin model. RunPod charges $3.59 per H200 hour directly, while AWS markup adds institutional overhead. CoreWeave's bulk configurations offer lower per-GPU costs for teams deploying multiple units simultaneously.

Availability matters greatly when comparing providers. AWS guarantees infrastructure access through service level agreements and capacity reservations. RunPod operates shared infrastructure with variable availability. CoreWeave prioritizes production customers with guaranteed allocation. Vast.AI offers no uptime guarantees but often provides the lowest pricing through peer-to-peer marketplaces.

Integration with AWS services provides compelling advantages for teams already investing in the ecosystem. S3 storage integrates smoothly with EC2 instances. AWS Lambda can orchestrate instance lifecycles automatically. RDS and DynamoDB integrate natively with EC2 workloads. These ecosystem benefits justify premium pricing for teams leveraging multiple AWS services.

Support quality and SLA guarantees differ across providers. AWS offers 24/7 technical support at multiple tiers, with faster response times for higher-tier customers. RunPod provides community support and documentation but limited direct assistance. CoreWeave targets production customers with dedicated support engineers. Teams requiring guaranteed uptime typically favor AWS or CoreWeave.

Review AWS GPU pricing for comprehensive comparison across instance types. Check H200 specifications to understand hardware capabilities. Explore GPU pricing guide for broader market analysis.

FAQ

Q: Does AWS offer H200 instances in all regions?

A: No. H200 availability varies by region and changes over time. us-east-1, us-west-2, and eu-west-1 typically offer H200 access. Check the AWS EC2 instance availability tool before planning workloads. Requests to AWS support can reserve capacity in specific regions if needed.

Q: Can I use AWS H200s with Hugging Face models?

A: Yes. AWS provides deep learning AMIs with PyTorch, TensorFlow, and CUDA pre-installed. Hugging Face libraries install via pip without issues. Model downloads from the Hub complete at reasonable speeds using EC2's high-bandwidth networking.

Q: What's the typical cost difference between H200 and H100 on AWS?

A: H200 instances cost roughly 50-70 percent more than H100 equivalents. The expanded memory justifies the premium for large models and long sequences. Smaller models may not utilize the additional capacity, making H100s more cost-effective for those workloads.

Q: Does AWS offer spot pricing for H200s?

A: Yes. Spot instances with H200 GPUs offer 60-75 percent discounts compared to on-demand pricing. Spot capacity is unpredictable and can be interrupted without warning. Fault-tolerant workloads like batch training benefit greatly from spot instances. Interactive workloads require on-demand or reserved instances for reliability.

Q: How do I connect an H200 instance to S3 for data loading?

A: EC2 instances have native S3 integration through IAM roles. Attach an IAM role with S3 permissions to the instance during creation. Use boto3 or AWS CLI to download training data directly from S3. No additional configuration is necessary.

Understanding GPU selection criteria helps match hardware to workload demands. Pricing comparison across providers ensures cost-effective infrastructure choices. Performance benchmarks guide decisions on when higher-tier GPUs justify expense.

Review H100 specifications to understand the previous generation. Check H200 specifications for detailed hardware capabilities. Study fine-tuning guide to understand common H200 use cases.

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