H100 SXM5 on Ori
Visit OriOri's NVIDIA H100 SXM5 offering combines a premier enterprise-grade GPU with a specialized edge-to-cloud orchestration platform, making it ideal for ML engineers tackling distributed AI workloads across multi-cloud and edge environments. The H100 SXM5, built on NVIDIA's Hopper architecture, features 80GB of HBM3 VRAM, delivering exceptional performance for large-scale training, inference, and HPC tasks with up to 4x faster AI inference over previous generations via Transformer Engine and FP8 precision. Ori's Cloud-to-Edge architecture enables seamless orchestration, allowing users to deploy and manage H100-powered instances from central clouds to distributed edge nodes without vendor lock-in. Key value propositions include per-second billing for cost optimization, native support for multi-cloud bursting, and edge AI capabilities for low-latency inference. This setup targets teams building scalable AI pipelines requiring flexibility, such as autonomous systems, real-time analytics, and federated learning, where traditional cloud providers fall short on edge integration. While Ori excels in orchestration, users should verify provider-specific benchmarks for peak throughput.
Why NVIDIA H100 SXM5 on Ori?
Choose Ori for NVIDIA H100 SXM5 if your workflows demand fluid scaling between cloud data centers and edge devices. Ori's Cloud-to-Edge platform uniquely orchestrates H100 instances across multi-cloud providers and on-premises edge hardware, leveraging the GPU's Hopper architecture for massive parallelism in AI training and inference. Per-second billing minimizes costs for bursty workloads, complementing H100's efficiency in handling trillion-parameter models. Unlike siloed GPU clouds, Ori provides unified management APIs, container orchestration, and edge deployment tools, reducing complexity for hybrid environments. This combination shines for edge AI applications like robotics or IoT, where H100's 80GB VRAM powers real-time processing without latency penalties from cloud-only setups.
Live Pricing
Real-time NVIDIA H100 SXM5 offers from Ori
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
![]() Ori | NVIDIA H100 SXM5 80GB VRAM | 80GB | 24 vCPU 240GB RAM 3000GB Storage | Seattle | $2.90/GPU/hr | Sold Out | ||
![]() Ori | 4×NVIDIA H100 SXM5 80GB VRAM | 80GB | 96 vCPU 960GB RAM 4000GB Storage | 🌍global | $2.90/GPU/hr $11.60/hr total (4×) | Sold Out | ||
![]() Ori | 4×NVIDIA H100 SXM5 80GB VRAM | 80GB | 96 vCPU 960GB RAM 4000GB Storage | Dallas | $2.90/GPU/hr $11.60/hr total (4×) | Sold Out | ||
![]() Ori | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 1920GB RAM 3000GB Storage | 🌍global | $2.90/GPU/hr $23.20/hr total (8×) | Sold Out | ||
![]() Ori | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 1920GB RAM 3000GB Storage | Seattle | $2.90/GPU/hr $23.20/hr total (8×) | Sold Out |





Performance Notes
On Ori, expect NVIDIA H100 SXM5 to deliver flagship Hopper performance: up to 4 petaFLOPS FP8 AI compute, 80GB HBM3 at 3.35 TB/s bandwidth, ideal for LLMs and diffusion models. Multi-GPU scaling via NVLink (900 GB/s bidirectional) supports efficient DGX-like clusters, but Ori-specific interconnect speeds (e.g., InfiniBand/RoCE) are not publicly detailed—assume standard data center norms unless benchmarked. Storage options likely include high-IOPS NVMe for checkpoints; edge deployments may limit to local SSDs. Network bandwidth supports cloud bursting, but edge nodes could cap at 100 Gbps. Real-world MLPerf scores apply, though provider overhead from orchestration may add minor latency—recommend user benchmarks for custom stacks.
A provider focused on edge-to-cloud orchestration for multi-cloud and edge AI.
Best For
Unique Features
- Cloud-to-Edge platform architecture
VRAM
80GB
Architecture
Hopper
Tier
enterprise
Platform Features
Getting Started
Getting started with NVIDIA H100 SXM5 on Ori is straightforward via their Cloud-to-Edge dashboard. Sign up for an account, select H100 configurations, and deploy instances with pre-built ML images. Leverage per-second billing and orchestration tools for quick scaling from cloud to edge, optimized for Docker/Kubernetes workflows.
Steps
- 1Create an Ori account and verify payment for per-second billing access.
- 2Navigate to the dashboard, select NVIDIA H100 SXM5, and choose instance size (e.g., 1-8 GPUs).
- 3Configure OS/image (Ubuntu with CUDA 12+), storage, and network; deploy with one-click.
- 4SSH or use web console to access; install frameworks like PyTorch via NGC containers.
- 5Scale to multi-cloud/edge via Ori Orchestrator API or UI for production workloads.
Pro Tips
- Use Ori's edge simulators during dev to test H100 inference latency before full deployment.
- Enable auto-scaling policies in the orchestrator to burst H100 cloud instances during training peaks.
- Monitor GPU utilization with DCGM exporter integrated in Ori for proactive optimization.
Frequently Asked Questions
What is Ori's billing model for NVIDIA H100 SXM5?▾
Ori bills per-second for GPU instances including NVIDIA H100 SXM5. Per-second billing ensures you only pay for exactly the compute time you use, which is particularly cost-effective for short experiments, iterative development, and workloads with variable duration.
Does Ori offer spot instances for NVIDIA H100 SXM5?▾
No, Ori does not currently offer spot instances for NVIDIA H100 SXM5. 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.
How can I access NVIDIA H100 SXM5 instances on Ori?▾
Ori provides access to NVIDIA H100 SXM5 instances via SSH, built-in Jupyter notebooks, web-based terminal. The built-in Jupyter notebook support makes it easy to start experimenting immediately without additional setup. SSH access gives you full control over the instance for custom configurations and production deployments.
What compliance certifications does Ori have for NVIDIA H100 SXM5 workloads?▾
Ori maintains SOC 2, GDPR, ISO 27001 certifications, making it suitable for regulated workloads. SOC 2 certification demonstrates strong security controls for handling sensitive data. Contact Ori directly for detailed compliance documentation and BAA agreements if needed.
Can I use NVIDIA H100 SXM5 with Kubernetes on Ori?▾
Yes, Ori supports Kubernetes for orchestrating NVIDIA H100 SXM5 workloads. This enables you to deploy scalable ML pipelines, manage distributed training jobs across multiple GPUs, and integrate with MLOps tools like Kubeflow, Argo Workflows, and KServe. Kubernetes support is essential for teams building production-grade ML infrastructure.
What are the specifications of the NVIDIA H100 SXM5?▾
The NVIDIA H100 SXM5 features 80GB of high-bandwidth memory, built on NVIDIA's Hopper architecture. As an enterprise-tier GPU, it's designed for large-scale AI training, inference at scale, and demanding HPC workloads. The substantial VRAM capacity supports large language models, complex neural networks, and multi-model deployments.
What workloads is NVIDIA H100 SXM5 on Ori best suited for?▾
The NVIDIA H100 SXM5 on Ori is well-suited for large-scale AI/ML training, LLM fine-tuning, batch inference at scale, and high-performance computing workloads. Ori specifically excels at: Multi-cloud and edge AI orchestration. Consider your model size, training data volume, and latency requirements when evaluating this combination for your specific use case.
Does Ori offer reserved instances for NVIDIA H100 SXM5?▾
Yes, Ori offers reserved instance pricing for NVIDIA H100 SXM5, 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 Ori for current reserved pricing and commitment terms.
What unique features does Ori offer for NVIDIA H100 SXM5?▾
Ori differentiates itself with: Cloud-to-Edge platform architecture. These features may provide advantages depending on your specific workflow requirements and technical needs. Evaluate how these capabilities align with your ML infrastructure goals when making your decision.
How do I get started with NVIDIA H100 SXM5 on Ori?▾
To get started with NVIDIA H100 SXM5 on Ori, visit https://ori.co?utm_source=gpuperhour&utm_medium=referral to create an account. Most providers offer a straightforward signup process, and some provide initial credits for new users. Once registered, you can typically launch a NVIDIA H100 SXM5 instance within minutes through their dashboard or API. We recommend starting with a small experiment to familiarize yourself with the platform before scaling up to larger workloads.
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