H100 SXM5 on VERDA
Visit VERDAVERDA provides the NVIDIA H100 SXM5 GPU, featuring 80GB HBM3 VRAM and Hopper architecture, optimized for enterprise AI, ML training, and HPC workloads. This combination stands out due to VERDA's pioneering green computing model, repurposing data center waste heat for district heating in Europe, significantly reducing environmental impact. Ideal for sustainability-focused ML engineers, data scientists, and organizations with ESG mandates, it offers top-tier performance without compromising on eco-responsibility. Key value propositions include per-hour billing for flexible, pay-as-you-go economics; access to the H100's Transformer Engine for 4x faster large language model training compared to A100s; and a European data sovereignty edge. VERDA targets sustainable AI training, blending high throughput (up to 3,958 TFLOPS FP8) with verifiable green credentials, making it a compelling choice for cost-conscious, planet-friendly scaling.
Why NVIDIA H100 SXM5 on VERDA?
Opt for VERDA's H100 SXM5 if sustainability drives your GPU decisions. Their waste heat recovery for district heating delivers genuine green impact, unlike marketing claims elsewhere, perfect for EU-based teams under carbon regulations. Per-hour billing enables bursty ML workloads without overcommitment, complementing the H100's efficiency in multi-trillion parameter models. VERDA's Europe-centric infrastructure ensures low-latency regional access and compliance, enhancing Hopper's NVLink scaling for distributed training. This duo excels for eco-aware enterprises needing enterprise-tier reliability—stable power from sustainable sources minimizes downtime—while flexible pricing undercuts locked-in contracts, offering unmatched value for intermittent high-compute AI pipelines.
Live Pricing
Real-time NVIDIA H100 SXM5 offers from VERDA
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 VERDA | 4×NVIDIA H100 SXM5 80GB VRAM | 80GB | 176 vCPU 740GB RAM | Finland | $2.29/GPU/hr $9.16/hr total (4×) | Sold Out | ||
VERDA | NVIDIA H100 SXM5 80GB VRAM | 80GB | 32 vCPU 170GB RAM | Helsinki | $3.27/GPU/hr | Available | ||
VERDA | 2×NVIDIA H100 SXM5 80GB VRAM | 80GB | 80 vCPU 340GB RAM | Helsinki | $3.27/GPU/hr $6.53/hr total (2×) | Available | ||
VERDA | NVIDIA H100 SXM5 80GB VRAM | 80GB | 30 vCPU 120GB RAM | Helsinki | $3.27/GPU/hr | Available | ||
VERDA | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 176 vCPU 1360GB RAM | Helsinki | $3.27/GPU/hr $26.13/hr total (8×) | Available |
Performance Notes
Expect flagship H100 SXM5 performance on VERDA: 80GB VRAM handles massive models, with Hopper's FP8 delivering ~4x A100 training speed via Transformer Engine. Multi-GPU scaling likely leverages NVLink (900GB/s) or InfiniBand, but VERDA-specific bandwidth/storage details are undocumented—assume enterprise-standard NVMe for I/O. Green cooling may yield thermal stability for sustained loads, aiding long trainings. No public MLPerf benchmarks available; real-world throughput depends on instance sizing. Strengths: efficient power use aligns with VERDA's model. Limitations: unverified networking could bottleneck exascale jobs—test for your workload.
A provider focused on green computing using waste heat for district heating.
Best For
Unique Features
- Use of waste heat for district heating
- Green computing focus
VRAM
80GB
Architecture
Hopper
Tier
enterprise
Platform Features
Getting Started
Launching NVIDIA H100 SXM5 on VERDA is user-friendly for ML pros. Sign up, configure instances via their dashboard, and deploy with pre-built CUDA images. Focus on sustainable monitoring tools while scaling AI jobs efficiently in Europe.
Steps
- 1Sign up on VERDA's website and add a payment method for per-hour billing.
- 2Access the GPU catalog, select H100 SXM5, and pick vCPU/RAM/storage config.
- 3Review pricing, set up SSH keys or Jupyter access, then launch the instance.
- 4Connect via SSH, pull NVIDIA CUDA Docker images, and run your workload.
- 5Monitor usage and sustainability metrics from the VERDA console.
Pro Tips
- Track waste heat reuse metrics in VERDA's dashboard to quantify your green impact for ESG reports.
- Pair with Kubernetes for auto-scaling multi-H100 clusters, optimizing per-hour costs for variable loads.
- Enable H100's MIG mode for concurrent inference/training, maximizing 80GB VRAM utilization.
Frequently Asked Questions
What is VERDA's billing model for NVIDIA H100 SXM5?▾
VERDA bills per-hour for GPU instances including NVIDIA H100 SXM5. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does VERDA offer spot instances for NVIDIA H100 SXM5?▾
No, VERDA 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.
Does VERDA offer reserved instances for NVIDIA H100 SXM5?▾
Yes, VERDA 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 VERDA for current reserved pricing and commitment terms.