H100 SXM5 on Cirrascale
Visit CirrascaleCirrascale's NVIDIA H100 SXM5 offering delivers 80GB Hopper architecture GPUs on bare-metal dedicated servers, tailored for AI innovation, deep learning, and HPC research. This enterprise-tier GPU excels in accelerated computing, providing breakthrough performance for large-scale model training, inference, and simulations with its Transformer Engine and FP8 precision support. Noteworthy for its non-virtualized deployment, eliminating overhead and ensuring consistent multi-GPU scaling without noisy neighbors—critical for long-running jobs. Targeted at research teams and ML engineers needing reliable, high-throughput environments, it stands out via Cirrascale's diverse hardware stack (NVIDIA, AMD, Qualcomm accelerators) and monthly billing for predictable costs on extended workloads. Key value propositions include dedicated performance isolation, seamless multi-node scaling for distributed training, and focus on innovation cloud infrastructure, making it ideal for teams prioritizing stability over on-demand flexibility. While specifics like exact interconnects are provider-dependent, this combo promises low-latency, high-bandwidth operations suited to demanding AI pipelines.
Why NVIDIA H100 SXM5 on Cirrascale?
Choose Cirrascale for NVIDIA H100 SXM5 to leverage bare-metal dedicated servers, avoiding virtualization overhead for maximum GPU utilization and consistent performance in multi-GPU setups. This complements the H100's Hopper strengths—80GB HBM3 VRAM, NVLink interconnects, and 4th-gen Tensor Cores—ideal for long-training jobs where stability trumps bursty usage. Cirrascale's AI Innovation Cloud emphasizes non-virtualized hardware, diverse accelerators for hybrid workflows, and monthly billing that aligns with research budgets, reducing costs for sustained runs versus hourly models. Unique advantages include dedicated HPC-grade infrastructure, no resource contention, and support for deep learning/HPC, enabling efficient scaling across nodes without performance variability common in shared clouds.
Live Pricing
Real-time NVIDIA H100 SXM5 offers from Cirrascale
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 39738GB Storage | United States | $2.49/GPU/hr $19.92/hr total (8×) | |||
Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 37523GB Storage | United States | $3.43/GPU/hr $27.44/hr total (8×) | |||
Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 37523GB Storage | United States | $3.85/GPU/hr $30.80/hr total (8×) | |||
Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 37523GB Storage | United States | $4.07/GPU/hr $32.56/hr total (8×) | |||
Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 37523GB Storage | United States | $4.28/GPU/hr $34.24/hr total (8×) |
Performance Notes
On Cirrascale, expect NVIDIA H100 SXM5 to deliver peak Hopper performance: up to 4 petaFLOPS FP8 AI, 60 TFLOPS FP64 for HPC, with 80GB HBM3 at 3.35 TB/s bandwidth. Bare-metal ensures full NVLink 900 GB/s GPU-to-GPU throughput and optimal multi-GPU scaling via NCCL or MPI. Network bandwidth likely InfiniBand or high-speed Ethernet (exact specs unconfirmed publicly), supporting efficient distributed training. Storage options include fast NVMe SSDs for datasets, though IOPS/latency details are provider-specific. Known strengths: consistent low-jitter for long jobs; limitations: monthly commitments may not suit short tasks, and real-world benchmarks depend on config—test via trial if available.
An AI Innovation Cloud targeting deep learning and HPC research with dedicated performance on non-virtualized hardware.
Best For
Unique Features
- Diverse hardware stack including Qualcomm, AMD, and NVIDIA accelerators
- Bare-metal dedicated servers
VRAM
80GB
Architecture
Hopper
Tier
enterprise
Platform Features
Getting Started
Getting started with Cirrascale's NVIDIA H100 SXM5 is straightforward for bare-metal GPU access. Sign up for a monthly dedicated server, deploy pre-configured images with CUDA 12+, and scale to multi-GPU/node clusters. Suited for experienced ML users; expect SSH/root access for custom environments like PyTorch or TensorFlow.
Steps
- 1Create account on Cirrascale website and verify for bare-metal access.
- 2Select NVIDIA H100 SXM5 config (e.g., 8x GPU server) and monthly billing.
- 3Deploy instance via dashboard; wait 5-30 min for provisioning.
- 4SSH into server, install NVIDIA drivers/CUDA if needed, and load Docker/nvidia-docker.
- 5Run benchmarks (e.g., MLPerf) and launch training jobs with multi-GPU flags.
Pro Tips
- Optimize multi-GPU with NCCL backend and NVLink awareness for 90%+ scaling efficiency on long jobs.
- Use DCGM for real-time monitoring of GPU utilization, temps, and power to avoid throttling.
- Pair with Cirrascale's high-speed storage tiers for dataset caching, minimizing I/O bottlenecks in training.
Frequently Asked Questions
What is Cirrascale's billing model for NVIDIA H100 SXM5?▾
Cirrascale bills monthly for GPU instances including NVIDIA H100 SXM5. Monthly billing is best suited for long-running, steady-state workloads where you need consistent access to GPU resources.
Does Cirrascale offer spot instances for NVIDIA H100 SXM5?▾
No, Cirrascale 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 Cirrascale?▾
Cirrascale provides access to NVIDIA H100 SXM5 instances via SSH. SSH access gives you full control over the instance for custom configurations and production deployments.
What compliance certifications does Cirrascale have for NVIDIA H100 SXM5 workloads?▾
Cirrascale does not have publicly listed compliance certifications. If your workloads require specific compliance standards (SOC 2, HIPAA, GDPR, etc.), contact them directly to discuss your requirements or consider a provider with the necessary certifications.
Can I use NVIDIA H100 SXM5 with Kubernetes on Cirrascale?▾
Yes, Cirrascale 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 Cirrascale best suited for?▾
The NVIDIA H100 SXM5 on Cirrascale is well-suited for large-scale AI/ML training, LLM fine-tuning, batch inference at scale, and high-performance computing workloads. Cirrascale specifically excels at: Research teams needing consistent, non-virtualized multi-GPU performance for long-training jobs. Consider your model size, training data volume, and latency requirements when evaluating this combination for your specific use case.
Does Cirrascale offer reserved instances for NVIDIA H100 SXM5?▾
Yes, Cirrascale 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 Cirrascale for current reserved pricing and commitment terms.
What unique features does Cirrascale offer for NVIDIA H100 SXM5?▾
Cirrascale differentiates itself with: Diverse hardware stack including Qualcomm, AMD, and NVIDIA accelerators; Bare-metal dedicated servers. 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 Cirrascale?▾
To get started with NVIDIA H100 SXM5 on Cirrascale, visit https://www.cirrascale.com?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.
Related Pages
Rent NVIDIA H100 SXM5
AWS vs Cirrascale: GPU Cloud Comparison
Cirrascale vs CoreWeave: GPU Cloud Comparison
Cirrascale vs Crusoe: GPU Cloud Comparison
NVIDIA A100 PCIe 40GB on Cirrascale - Pricing & Availability
NVIDIA A100 PCIe 80GB on Cirrascale - Pricing & Availability
NVIDIA B200 SXM on Cirrascale - Pricing & Availability
NVIDIA H200 SXM on Cirrascale - Pricing & Availability
AMD Instinct MI250X on Cirrascale - Pricing & Availability
NVIDIA H100 SXM5 in Canada - Pricing & Availability
NVIDIA H100 SXM5 in California, United States - Pricing & Availability
NVIDIA H100 SXM5 in Czechia - Pricing & Availability
NVIDIA H100 SXM5 in Dallas, Texas, United States - Pricing & Availability
NVIDIA H100 SXM5 in Dallas, United States - Pricing & Availability