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Hyperstack GPU Cloud Pricing: Complete Guide vs Hourly Rates for Every GPU

Deploybase · December 5, 2025 · GPU Pricing

Contents

Overview

Hyperstack runs European GPUs. Competitive rates. Focuses on multi-GPU and batch work.

Hyperstack Pricing Models

Transparent hourly rates. No hidden fees. Easy budgeting.

On-Demand Pricing Structure

Hyperstack pricing tiers reflect underlying hardware costs:

  • H100 80GB: Highest tier pricing for maximum performance
  • A100 40GB/80GB: Mid-range options for flexible budgets
  • RTX 4090: Consumer-grade GPUs for inference and development
  • Older generation GPUs: Discounted legacy inventory

The platform encourages monthly billing for cost predictability. Annual commitments provide modest 5-10% discounts.

Regional Availability

Hyperstack maintains primary data centers in Frankfurt, Amsterdam, and London. US-based customers experience higher latency and potential regional markup. Pricing adjusts slightly by location, typically within 10% variance.

GPU Availability

H100 Inventory

Hyperstack maintains consistent H100 stock across European regions. Per-GPU hourly pricing for H100 SXM is approximately $2.40/hour, with standard H100 at $1.90-$1.95/hour. Frankfurt (FRA) data centers command lowest pricing while London (LON) facilities run approximately 5-8% premium.

H100 80GB configurations provide 67 TFLOPS FP32 (1,979 TFLOPS FP16 Tensor Core) and 3,350GB/sec memory bandwidth. These specifications suit large language model training with batch sizes 16-32 on single-GPU instances. Hyperstack's inventory typically includes both HBM3 and older HBM2 variants, with HBM3 commanding modest price premiums.

Comparing against Lambda GPU pricing at $3.78/hour for H100 SXM highlights Hyperstack's positioning. At $1.90-$2.40/hour for H100, Hyperstack is significantly cheaper than Lambda while offering EU data residency advantages for teams with GDPR requirements. Teams targeting EU customer bases benefit from geographic co-location and reduced network latency. GDPR-compliant data residency in Frankfurt adds value for regulated industries processing EU customer data.

Multi-GPU Clusters

Hyperstack specializes in pre-configured GPU clusters optimized for training workloads. An 8×H100 SXM setup costs approximately $19.20/hour (8 × $2.40), providing significant savings versus individual GPU pricing. These clusters include dedicated networking with 400Gbps interconnect fabric, enabling efficient distributed training.

Configuration options range from 2×H100 ($4.80/hour) through 16×H100 ($38.40/hour) in standard increments. Custom configurations above 16 GPUs require custom engineering quotes.

This contrasts with CoreWeave GPU pricing at $49.24/hour for 8×H100, showing 60%+ cost difference for multi-GPU deployments. The gap widens for larger clusters. Hyperstack's 16×H100 cluster at approximately $38.40/hour costs roughly 70% less than equivalent CoreWeave capacity.

Bandwidth Considerations

All Hyperstack plans include generous bandwidth allocations. Outbound traffic pricing applies only beyond monthly thresholds, typically 100-500GB depending on package tier and instance size. Inbound traffic to Hyperstack infrastructure carries zero cost, important for teams ingesting large training datasets.

A single H100 instance includes approximately 200GB monthly outbound allowance. Exceeding this threshold costs $0.08-$0.12 per GB, reasonable for moderate-bandwidth workloads. Large data transfer projects should negotiate custom bandwidth terms with Hyperstack's sales team.

Cost Comparison

Monthly Operating Costs

Running a single H100 SXM continuously:

  • Hyperstack hourly: $2.40 (H100 SXM pricing)
  • Monthly cost: 30 × 24 × $2.40 = $1,728
  • Annual cost: $20,736

This represents competitive pricing versus US-based providers like Lambda ($2.49/hour). Additional storage costs (approximately $0.12 per GB-month) add roughly $25-50 monthly for typical development workloads.

Training Workload Projections

A 500-hour training job on single H100 SXM:

  • Hyperstack cost: 500 × $2.40 = $1,200
  • Lambda GPU pricing H100 SXM cost: 500 × $3.78 = $1,890
  • Hyperstack is significantly cheaper than Lambda while offering EU data residency

A larger 2,000-hour continuous training workload:

  • Hyperstack: 2,000 × $2.40 = $4,800
  • Lambda H100 SXM: 2,000 × $3.78 = $7,560
  • AWS: 2,000 × $4.30 = $8,600
  • Hyperstack vs AWS savings: $3,800 (44%)
  • Hyperstack vs Lambda savings: $180 (4%)

Multi-GPU Training Scaling

8×H100 SXM cluster for a 200-hour distributed training job:

  • Hyperstack: 200 × $19.20 = $3,840
  • CoreWeave: 200 × $49.24 = $9,848
  • Savings: $6,008 (61%)

This 8-GPU scaling demonstrates Hyperstack's particular strength in multi-GPU training economics.

Inference Economics

Real-time inference workloads favor spot instances where available. Hyperstack's lack of spot pricing increases inference costs compared to AWS GPU pricing options with preemptible instances.

However, for containerized batch inference with known scheduling windows, Hyperstack's transparent pricing eliminates cost uncertainty. Running 10,000 inference requests in batch mode costs the same regardless of time-of-day or demand patterns.

Optimal Use Cases for Hyperstack

European Teams and GDPR Compliance

Hyperstack's Frankfurt headquarters and EU-focused infrastructure make it ideal for teams requiring GDPR compliance. Data residency in Frankfurt satisfies GDPR Article 44 requirements without complex cross-border transfer documentation.

Teams processing EU customer data benefit from simplified compliance processes. Traditional cloud providers' global infrastructure requires complex Data Processing Agreements and Standard Contractual Clauses. Hyperstack eliminates this complexity for EU-based operations.

European AI Research

Academic institutions and research labs targeting EU funding (Horizon Europe, EIC, etc.) benefit from Hyperstack's European positioning. Funders increasingly require data processing within European borders. Hyperstack simplifies grant compliance while maintaining competitive pricing.

Research teams particularly value Hyperstack's technical support team's understanding of ML frameworks and distributed training patterns. Customer support engineers typically hold advanced degrees in machine learning, providing better guidance than generic cloud support.

Multi-Region European Deployments

Teams operating across multiple European markets should evaluate Hyperstack's regional availability. Three data centers (Frankfurt, Amsterdam, London) provide redundancy within the region while maintaining lower costs than global providers.

Deploying primary workloads in Frankfurt with failover to Amsterdam ensures GDPR compliance while providing geographic redundancy. Total cost for dual-region deployment remains lower than equivalent AWS infrastructure.

Cost-Sensitive Development Teams

Startups and bootstrapped teams benefit significantly from Hyperstack's 15-25% cost advantage over US-based providers. Developing and validating models on Hyperstack before production deployment on Alibaba Cloud or RunPod represents sound cost optimization.

A team training multiple Llama 2 variants saves approximately $10,000-20,000 monthly on Hyperstack versus AWS, enabling reinvestment in additional model experiments or infrastructure optimization. Versus Lambda, costs are comparable with Hyperstack offering EU data residency advantages.

European GPU Market Analysis

Regulatory Compliance Advantage

Hyperstack's European base provides inherent advantages for regulated industries. GDPR compliance requires demonstrating personal data never leaves the EU. Hyperstack's Frankfurt data centers satisfy this requirement without expensive cross-border transfer infrastructure.

Comparing AWS GPU pricing where US regions dominate, European teams requiring GDPR compliance face forced regional deployment at premium pricing. Hyperstack eliminates this regulatory tax.

Competing with US Cloud Giants

Despite US dominance in cloud infrastructure, Hyperstack competes effectively in Europe through:

  1. 20-25% cost advantage over AWS European regions
  2. GDPR-native infrastructure design (not retrofitted compliance)
  3. ML-focused technical support understanding distributed training challenges
  4. No geographic latency to EU customer bases

A typical GDPR-compliant ML inference deployment:

  • Hyperstack Frankfurt: $2,500-3,500/month
  • AWS eu-central-1: $4,000-5,000/month
  • Azure West Europe: $4,200-5,200/month

Hyperstack saves 30-40% annually for companies with mandatory EU data residency.

Integration with European AI Initiatives

Hyperstack participates in EU AI Act compliance infrastructure. Their infrastructure design anticipates regulatory requirements around AI transparency and auditability. This forward-looking compliance positioning appeals to companies building regulated AI systems.

FAQ

Q: Does Hyperstack offer spot or preemptible instances? A: Hyperstack does not provide spot pricing. All instances are full-rate on-demand only.

Q: What's the minimum contract duration? A: Hourly billing is available without minimum commitments. Monthly billing discounts apply even for single-month terms.

Q: How quickly can new instances launch? A: Most GPUs provision within 2-5 minutes. During peak hours (EU business hours), delays may extend to 10-15 minutes.

Q: Does Hyperstack support mixed GPU clusters? A: Yes. Custom configurations mixing H100, A100, and L40S GPUs are possible but require manual setup.

Q: What security certifications does Hyperstack hold? A: Hyperstack maintains ISO 27001 and SOC 2 Type II certifications covering data protection and access control.

Sources

  • Hyperstack official pricing page (as of March 2026)
  • European data center infrastructure reports
  • GPU availability surveys
  • DeployBase infrastructure research