Rent NVIDIA GH200 Grace Hopper Cloud Instances
📊 Pricing at a Glance
NVIDIA GH200 Grace Hopper rental pricing ranges from $1.99/GPU/hr to $6.50/GPU/hr across 14 instances from 4 providers (updated June 2026).
Looking for a specific provider? See Vultr NVIDIA GH200 Grace Hopper, Lambda Labs NVIDIA GH200 Grace Hopper, or Denvr NVIDIA GH200 Grace Hopper.
Available Offers
Compare the top 5 cheapest offers from 4 providers.
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
 Denvr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 7600GB Storage | Virginia | $3.87/GPU/hr | |||
 CoreWeave | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 7680GB Storage | United States | $6.50/GPU/hr | |||
Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | 🌍global | $1.99/GPU/hr | Sold Out |
QuantaCloud
H-series supply is constrained.
Most providers are sold out through Q3 2026. If you need 16+ GPU reserved or cluster capacity in the next 90 days, we can quote B300 or remaining Hopper inventory within 24 hours.
Technical Specifications
Strengths & Limitations
- Exceptional performance for HPC and AI workloads due to the Grace CPU and Hopper GPU integration.
- Unified memory architecture (NVLink-C2C) provides significantly faster data transfer between CPU and GPU compared to traditional PCIe connections.
- High memory bandwidth with HBM3 memory enables processing of large datasets.
- Optimized for large language models (LLMs) and other memory-intensive applications.
- Energy-efficient design compared to discrete CPU and GPU solutions.
- High cost compared to other GPU options.
- Limited availability due to its cutting-edge technology.
- Requires specialized software and infrastructure to fully utilize its capabilities.
- May not be suitable for all types of workloads; excels in memory-bound and tightly coupled CPU-GPU tasks.
Top Use Cases
The GH200's unified memory and high bandwidth are ideal for training and deploying massive LLMs, enabling faster iteration and improved model accuracy.
Scientific simulations in fields like climate modeling, drug discovery, and materials science benefit from the GH200's computational power and memory capacity.
The GH200 accelerates data processing and model training for complex analytics tasks, enabling faster insights and improved decision-making.
Real-World Benchmark
Market Analysis
The NVIDIA GH200 Grace Hopper occupies a premium segment of the cloud GPU market, targeting users with the most demanding HPC and AI workloads. Its high price reflects its cutting-edge technology and exceptional performance. Compared to other high-end GPUs like the NVIDIA H100 ($1.07/hr for PCIe, $0.74/hr for SXM5, $1.87/hr for NVL) and H200 ($0.50/hr for NVL, $1.90/hr for SXM), the GH200 offers a unique CPU-GPU integration that can provide significant advantages for specific applications. The AMD Instinct MI300X ($0.50/hr) is a competitor in the HPC/AI space, but lacks the tight CPU-GPU integration of the GH200.
Frequently Asked Questions
What is the key advantage of the GH200 Grace Hopper?▾
The key advantage is its unified memory architecture, which allows for significantly faster data transfer between the CPU and GPU compared to traditional systems.
What types of workloads are best suited for the GH200?▾
The GH200 is best suited for memory-intensive HPC and AI workloads, such as large language model training, scientific simulations, and data analytics.
Is the GH200 energy-efficient?▾
Yes, the GH200 is designed to be more energy-efficient than discrete CPU and GPU solutions due to its integrated architecture.
Alternative GPUs
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