GH200 Grace Hopper on Vultr
Visit VultrVultr's NVIDIA GH200 Grace Hopper Superchip offering delivers enterprise-grade accelerated computing to a globally distributed cloud platform spanning 32+ regions. The GH200 integrates a 72-core NVIDIA Grace Arm CPU with a Hopper GPU featuring 96GB HBM3 VRAM, interconnected via 900 GB/s NVLink-C2C for fully coherent 576GB total memory. This eliminates traditional CPU-GPU data transfer bottlenecks, enabling unprecedented efficiency for trillion-parameter AI model training, inference, and HPC simulations like climate modeling or drug discovery. Target audience: ML engineers and data scientists at scale-up enterprises needing low-latency global deployments. Key value propositions include Vultr's massive footprint for edge-to-cloud workflows, per-hour billing for cost predictability, and integrated services like Kubernetes and managed databases. This combination empowers seamless scaling of memory-intensive workloads without sharding, offering 2-4x performance gains over discrete systems.
Why NVIDIA GH200 Grace Hopper on Vultr?
Vultr pairs perfectly with the GH200 due to its expansive 32+ region footprint, enabling low-latency distributed training and inference worldwide—ideal for global teams or multi-region AI pipelines. Hourly billing provides flexibility for bursty workloads, avoiding AWS/GCP-style commitments. High-speed NVMe block storage and object storage complement the Superchip's coherent memory for rapid dataset access. Vultr's integrated ecosystem, including VPC networking and managed K8s, simplifies orchestration of GH200 clusters. This setup leverages the GPU's HPC/AI prowess with provider strengths in geographic diversity and developer-friendly tools, outperforming regional providers while matching hyperscalers on accessibility.
Live Pricing
Real-time NVIDIA GH200 Grace Hopper offers from Vultr
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Manchester | $1.99/GPU/hr | Sold Out | ||
Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Amsterdam | $1.99/GPU/hr | Sold Out | ||
Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Amsterdam | $1.99/GPU/hr | Sold Out | ||
Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Frankfurt | $1.99/GPU/hr | Sold Out | ||
Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | New Jersey | $1.99/GPU/hr | Sold Out |
Performance Notes
Vultr's GH200 instances excel in single-node AI/HPC with NVLink-C2C enabling 900 GB/s CPU-GPU bandwidth and 576GB coherent memory, ideal for large language models without offloading. Multi-GPU scaling supported via Vultr's 100 Gbps+ public/private networking and emerging InfiniBand options for clusters. NVMe SSDs (up to 25 Gbps) handle high-IOPS datasets; object storage integrates for S3-compatible access. Benchmarks are limited pre-general availability, but expect H100-level FP8/FP16 throughput with 30-50% efficiency gains from coherence. Global regions minimize cross-region latency (<50ms). Unknowns: exact node interconnect speeds—monitor Vultr docs for updates.
A global cloud provider with a massive footprint for deployments across numerous regions.
Best For
Unique Features
- Massive global footprint
- Integrated cloud services
VRAM
96GB
Architecture
Hopper
Tier
enterprise
Platform Features
Getting Started
Getting started with Vultr's NVIDIA GH200 Grace Hopper is efficient via the intuitive cloud console. Choose from 32+ regions for optimal latency, deploy pre-built CUDA-enabled images, and scale instantly with hourly billing. Supports NVIDIA NGC for ML frameworks like PyTorch/TensorFlow out-of-the-box.
Steps
- 1Sign up or log in to the Vultr Cloud Console at cloud.vultr.com.
- 2Navigate to Products > Compute > GPU Droplets and select NVIDIA GH200 Grace Hopper.
- 3Pick a region/datacenter, instance size, add block storage, and configure networking.
- 4Choose OS/image (e.g., Ubuntu with CUDA), deploy, and wait ~5-10 minutes for provisioning.
- 5SSH into the instance (public IP/key) and verify with 'nvidia-smi' or NGC login.
Pro Tips
- Use NVIDIA NGC containers for pre-optimized CUDA/cuDNN stacks to accelerate framework setup and reproducibility.
- Enable Vultr's auto-scaling groups and hourly billing for cost-effective burst training; pair with spot instances if available.
- Monitor GPU utilization via Vultr Insights or Prometheus; tune NVLink with NVIDIA DCGM for peak coherent memory performance.
Frequently Asked Questions
What is Vultr's billing model for NVIDIA GH200 Grace Hopper?▾
Vultr bills per-hour for GPU instances including NVIDIA GH200 Grace Hopper. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Vultr offer spot instances for NVIDIA GH200 Grace Hopper?▾
No, Vultr does not currently offer spot instances for NVIDIA GH200 Grace Hopper. All instances are billed at on-demand rates. However, they do offer reserved instances for committed usage, which can provide significant discounts for long-term workloads.
Does Vultr offer reserved instances for NVIDIA GH200 Grace Hopper?▾
Yes, Vultr offers reserved instance pricing for NVIDIA GH200 Grace Hopper, which can provide significant discounts (typically 20-40% off on-demand rates) for committed usage periods. Reserved instances are ideal for predictable, long-running workloads like production inference services, ongoing training pipelines, or development environments that run continuously. Contact Vultr for current reserved pricing and commitment terms.
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