NVIDIA H200 SXM Guide: Specs, Pricing and How to Reserve Your GPU VM

What is NVIDIA H200 SXM

The NVIDIA H200 SXM is part of NVIDIA’s Hopper architecture GPU for AI, high-performance computing (HPC) and memory-intensive applications. It has a high-bandwidth memory of 141GB and 3,958 TFLOPS of FP8 compute for fast AI model training. These improvements are enabled by the hopper architecture on the base level, making the H200 SXM ideal for scaling up models like GPT, Llama 3.3 70B, Mistral, and other memory-hungry models.

Now, let’s look at how the H200 SXM is deployed on Hyperstack and what you get.

What are the Features of NVIDIA H200 SXM

When you deploy an NVIDIA H200 SXM VM on Hyperstack, you’re working in a real cloud environment built from the ground up to support demanding AI, ML and data workloads. Every part of the infrastructure is optimised to give you a production-grade experience from day one.

Scale Complex Models 

Each VM includes 8 NVIDIA H200 SXM GPUs, interconnected for high throughput and coordinated compute. This design allows you to train large transformer models, run memory-intensive simulations or process multi-modal datasets without splitting across multiple instances.

Having all eight GPUs available within one setup reduces latency between GPU communication and simplifies orchestration. This is especially beneficial for enterprise AI teams running distributed frameworks like DeepSpeed, Megatron-LM or Hugging Face Accelerate.

Accelerate Training and Inference 

Hyperstack enables high-speed networking for H200 SXM VMs, delivering up to 350 Gbps of bandwidth. This is critical for synchronising weights across GPUs during training, ingesting large datasets or moving data between storage and compute layers.

Workloads that rely on rapid, low-latency data movement such as fine-tuning LLMs or real-time streaming inference benefit from this network architecture, reducing both training time and cost.

Speed Up Data Access 

Each NVIDIA H200 SXM VM includes 32,000 GB of ephemeral NVMe storage, ensuring extremely fast data access and temporary caching capabilities. This local storage is ideal for managing training datasets, intermediate checkpoints and high-throughput I/O operations during job execution.

By eliminating I/O bottlenecks and reducing the reliance on external volumes, ephemeral NVMe improves model training efficiency and supports workflows with large data footprints.

Run Memory-Intensive Workloads

With 1.9 TB of system RAM, you can run large memory-dependent applications without the typical limitations of virtualised environments. This high RAM capacity is ideal for workloads such as real-time analytics, multi-threaded model evaluation and in-memory data preprocessing.

It allows you to keep entire datasets, inference pipelines, or application states in memory, helping reduce data fetch latency and increase throughput.

Restore Environments Instantly 

Hyperstack’s snapshot support lets you take point-in-time captures of your H200 SXM VM. These snapshots include the full state of the system, from OS configuration to bootable volumes, making it easy to recover environments, roll back after errors or maintain multiple version checkpoints for model testing.

This is valuable during experimentation or deployment cycles, when being able to restore a known-good environment can save you hours or even days of reconfiguration.

Keep Your Setup Intact 

Each NVIDIA H200 SXM VM includes a 100 GB bootable volume, where OS files and configurations are stored persistently. This allows you to maintain your preferred development setup, software stack, and scripts across restarts, making it easy to pick up right where you left off.

NVIDIA H200 SXM Pricing 

Hyperstack offers flexible GPU pricing to support both dynamic and long-term workloads. You can choose between on-demand access or reservation-based pricing depending on your workload.

On-Demand Access

You can access NVIDIA H200 SXM in minutes via the on-demand option. This is ideal for workloads that require immediate compute power for short-term workloads or testing environments.

• Price: $3.50/hour
• Billing: Pay-as-you-go, only for what you use
• Ideal For: Proof of concept, ad-hoc training, testing deployments or last-minute scaling

Reservation Option

For teams running consistent training jobs, long-term research projects or scalable deployment pipelines, reservations offer lower pricing with the same performance.

• Price: $2.45/hour
• Billing: Reserved pricing for a fixed duration
• Ideal For: Large-scale LLM training, production inference pipelines, academic research, and simulation-based workloads

Save Costs with Hibernation

If your NVIDIA H200 SXM VM is idle, you can hibernate it using the Hibernation Feature, retaining its state and reducing compute costs. It is ideal for projects with downtime or infrequent workloads. The best part is that you can resume operations instantly without setting up the environment again while also saving on idle compute costs.

Here’s how you can hibernate your H200 SXM VM on Hyperstack:

1. Go to the VM Details Page
   Start by navigating to the details page of the H200 SXM virtual machine you want to hibernate.
2. Access More Options
   In the top right corner of the window, hover your cursor over the "More Options" dropdown.
3. View Available Actions
   A list of VM state-changing actions will appear. These include options like  Stop, Hard reboot and Hibernate.
4. Click on Hibernate this VM
   Select "Hibernate this VM" from the list. This will transition your VM into a hibernated state.

How to Reserve Your NVIDIA H200 SXM VM

If you’re planning large-scale AI projects, short-term access to GPUs may not always be reliable, especially when demand peaks. Hyperstack allows you to reserve NVIDIA H200 SXM VMs in advance so you can prepare and future-proof your operations.

Here's how reservations can support your workload and how to get started.

Get Lower Pricing for Long-Term Workloads

When you're running projects that span weeks or months like training large language models or deploying continuous inference pipelines, cost predictability becomes crucial. With a reservation, you lock in a discounted hourly rate ($2.45/hour) for the entire reservation period of NVIDIA H200 SXM. Unlike on-demand usage, which may fluctuate in availability, reserved H200 SXM VMs ensure your budget remains aligned with your usage. 

Secure Access to In-Demand GPU Capacity

GPU demands continue to rise for advanced GPUs like the NVIDIA H200 SXM and NVIDIA H100 SXM. So often the availability can no longer be guaranteed during peak hours or time-sensitive deployment windows.

Reserving ensures that you always have access to the compute you need, when you need it. This is useful if you're working on product deadlines, training time-bound models or running jobs that can't afford interruptions.

Maintain Visibility with Usage Tracking

When you're using reserved capacity, it's important to know how much you've consumed, what’s remaining and how usage aligns with your project timeline. Hyperstack helps you stay on top of this with a Contract Usage tab in your billing portal.

This allows you to:

• Monitor real-time consumption of reserved H200 SXM hours
• Forecast remaining GPU hours
• Avoid overuse or idle waste

Reservation Process for NVIDIA H200 SXM

The reservation process is simple and can be completed in a few steps:

1. Visit the Reservation Page to reserve NVIDIA H200 SXM on Hyperstack

2. Complete the Form: Fill in your details, including:

• • Company Name
  • Use Case (e.g., LLM training, multimodal AI, inference)
  • Number of GPUs Required (e.g., 8, 16, 32)
  • Duration of Reservation (e.g., 1 month, 3 months, 6 months)

3. Submit Your Request

After submission, our team will contact you to finalise the reservation, discuss your workload requirements and ensure you get the best performance for your workloads..

Conclusion

The NVIDIA H200 SXM is one of the most popular choices to tackle demanding workloads required by modern day AI models and HPC applications. With Hyperstack, you get more than just access to this hardware, you get a complete environment in the cloud for enterprise performance and that too at flexible prices. 

No matter if you're just getting started or scaling production workloads, our H200 SXM VMs give you the speed, storage and scalability you need with easy deployment. You can even get started today, just head to the Hyperstack Console, choose your VM and launch in a few clicks.

Ready to Get Started?

Here are some helpful resources that will help you deploy your first VM on Hyperstack:

• New to Hyperstack? Sign up Today to Get Started

• Check out the Hyperstack API Documentation 

• Explore the Quick Platform Tour

• Need help? Contact us anytime at support@hyperstack.cloud 

FAQs

What is NVIDIA H200 SXM?

NVIDIA H200 SXM is a high-performance GPU built on Hopper architecture for large-scale AI, HPC and memory-intensive workloads.

What are the key features of NVIDIA H200 SXM?

NVIDIA H200 SXM on Hyperstack offers 8 GPUs per VM, 1920 GB RAM, 32 TB NVMe and 350 Gbps networking for enterprise-grade AI workloads.

What is the memory size of NVIDIA H200 SXM?

The NVIDIA H200 SXM has 141 GB of HBM3e memory, making it ideal for training large language and multi-modal AI models.

Can I run LLMs like GPT or Mistral on H200 SXM?

Yes, NVIDIA H200 SXM is ideal for large LLMs such as GPT, Llama 3.3, and Mistral due to its memory and compute.

What type of storage does H200 SXM VMs include?

Each VM includes 32 TB of fast ephemeral NVMe storage, ideal for caching, dataset loading, and checkpoint management.

What is the cost of NVIDIA H200 SXM?

The on-demand pricing for H200 SXM is $3.50/hour and reserved VMs cost $2.45/hour.

Can I reserve NVIDIA H200 SXM in advance?

Yes, Hyperstack allows GPU reservation so you get guaranteed access and discounted rates for long-term workloads.

How do I reserve H200 SXM on Hyperstack?

Visit the reservation page, fill in your details, submit the form and the Hyperstack team will assist you further.