H100 SXM5 on LeaderGPU
Visit LeaderGPULeaderGPU provides bare-metal NVIDIA H100 SXM5 GPUs with 80GB HBM3 VRAM, leveraging the Hopper architecture for top-tier AI, machine learning, and HPC workloads. This enterprise-grade offering stands out for its direct hardware access, eliminating virtualization overhead and delivering peak performance for large language model training, inference, and complex simulations. LeaderGPU's infrastructure emphasizes high-bandwidth networking and diverse GPU configurations, making it ideal for ML engineers and data scientists needing scalable compute without commitments. Key value propositions include flexible per-minute billing for on-demand usage, alongside weekly/monthly flat rates for sustained projects, rapid provisioning, and reliability suited to production environments. While optimized for hash cracking and rendering, the H100 SXM5 unlocks trillion-parameter model capabilities, offering cost-effective premium access in a bare-metal setup that prioritizes bandwidth and low latency over shared cloud abstractions.
Why NVIDIA H100 SXM5 on LeaderGPU?
LeaderGPU pairs exceptionally well with the NVIDIA H100 SXM5 due to its bare-metal servers, which provide unthrottled access to the GPU's full Hopper capabilities, including 80GB VRAM and high NVLink interconnects for multi-GPU scaling. High-bandwidth networking (InfiniBand or 100Gbps+ Ethernet) complements the H100's demands for distributed training, minimizing bottlenecks in AI workloads. Flexible billing—per-minute for bursty jobs or flat weekly/monthly rates—optimizes costs for expensive H100 rentals, unlike rigid hourly models. Provider strengths in diverse GPUs and quick deployment enable hybrid setups, while bare-metal ensures consistent performance for rendering or cracking tasks repurposed for ML. Ideal for users seeking raw power without cloud overhead.
Live Pricing
Real-time NVIDIA H100 SXM5 offers from LeaderGPU
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
![]() LeaderGPU | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 2048GB RAM 2000GB Storage | Netherlands | $5.20/GPU/hr $41.56/hr total (8×) | Sold Out |

Performance Notes
On LeaderGPU, expect the H100 SXM5 to deliver full specs: up to 4 PFLOPS FP8 AI performance, 80GB HBM3 at 3.35 TB/s bandwidth, and Hopper Transformer Engine for efficient large-model training. Bare-metal eliminates hypervisor losses, with high-bandwidth NVLink/SXM5 for 8-GPU scaling. Provider's infrastructure offers robust NVMe storage and 100Gbps+ networking, supporting low-latency multi-node jobs. Known strengths in high-throughput tasks like rendering confirm reliable perf, but exact interconnect details (e.g., IB speeds) and storage IOPS are provider-specific—verify via docs. No virtualization means optimal CUDA utilization; real-world ML benchmarks should match NVIDIA references.
A provider specializing in bare-metal servers with high bandwidth and diverse GPU availability.
Best For
Unique Features
- Flexible weekly/monthly flat-rate billing
- Diverse consumer GPU cards
VRAM
80GB
Architecture
Hopper
Tier
enterprise
Platform Features
Getting Started
LeaderGPU simplifies bare-metal H100 SXM5 access via an intuitive dashboard. Sign up, configure, deploy, and access in minutes with per-minute billing for flexibility. Suited for experienced users comfortable with SSH and GPU orchestration tools.
Steps
- 1Create a free account on the LeaderGPU website and verify email.
- 2Log in to the dashboard and navigate to 'Deploy GPU Server'.
- 3Select NVIDIA H100 SXM5 config, CPU/RAM/storage, and billing (per-min or flat).
- 4Review cost, confirm payment, and deploy—server ready in ~5-10 minutes.
- 5Connect via SSH (keys provided) or VNC; install NVIDIA drivers/CUDA as needed.
Pro Tips
- Pre-install Docker/NVIDIA Container Toolkit for seamless ML frameworks like PyTorch.
- Monitor resource usage via dashboard to optimize per-minute billing and avoid idle costs.
- Test multi-GPU scaling with NCCL benchmarks early to validate NVLink performance.
Frequently Asked Questions
What is LeaderGPU's billing model for NVIDIA H100 SXM5?▾
LeaderGPU bills per-minute for GPU instances including NVIDIA H100 SXM5. Check their pricing page for the most current billing details.
Does LeaderGPU offer spot instances for NVIDIA H100 SXM5?▾
No, LeaderGPU 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 LeaderGPU?▾
LeaderGPU provides access to NVIDIA H100 SXM5 instances via SSH, Docker containers. SSH access gives you full control over the instance for custom configurations and production deployments.
What compliance certifications does LeaderGPU have for NVIDIA H100 SXM5 workloads?▾
LeaderGPU maintains GDPR certification, making it suitable for regulated workloads. Contact LeaderGPU directly for detailed compliance documentation and BAA agreements if needed.
Can I use NVIDIA H100 SXM5 with Kubernetes on LeaderGPU?▾
LeaderGPU does not prominently advertise native Kubernetes support. You may need to manage your own Kubernetes cluster or use alternative orchestration methods. However, they do support Docker containers, which can be a stepping stone to container orchestration.
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 LeaderGPU best suited for?▾
The NVIDIA H100 SXM5 on LeaderGPU is well-suited for large-scale AI/ML training, LLM fine-tuning, batch inference at scale, and high-performance computing workloads. LeaderGPU specifically excels at: Hash cracking and rendering tasks. Consider your model size, training data volume, and latency requirements when evaluating this combination for your specific use case.
Does LeaderGPU offer reserved instances for NVIDIA H100 SXM5?▾
Yes, LeaderGPU 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 LeaderGPU for current reserved pricing and commitment terms.
What unique features does LeaderGPU offer for NVIDIA H100 SXM5?▾
LeaderGPU differentiates itself with: Flexible weekly/monthly flat-rate billing; Diverse consumer GPU cards. 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 LeaderGPU?▾
To get started with NVIDIA H100 SXM5 on LeaderGPU, visit https://www.leadergpu.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.
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