Organizations requiring high-performance computing infrastructure face two primary financial models: purchasing a system or renting one. Each approach carries distinct financial, operational, and strategic implications. This article compares both through concrete scenarios and provides a framework for determining which model best suits your organization.
The Purchase (CapEx) Model
The traditional approach: hardware is acquired upfront, installed, and becomes an organizational asset.
Advantages
- Lowest long-term cost: Over 5+ years of use, typically the least expensive option
- Full control: Unlimited flexibility over hardware and software configuration
- Data sovereignty: Sensitive data never leaves the premises
- Depreciation: Treated as an asset in corporate accounting
- Uninterrupted access: Not subject to service windows controlled by a third party
Disadvantages
- High upfront cost: A mid-scale cluster requires $500,000–$5,000,000+ capital
- Rapid technology change: 3–4 year GPU generation cycles partially devalue investments
- Operational burden: Requires dedicated HPC system administrator headcount
- Capacity planning risk: Over-provisioning is sunk cost; under-provisioning constrains work
- Power and space costs: Data center rent, cooling, and electricity add ongoing expense
Example Cost Breakdown (64 CPU + 8 GPU Node Cluster)
| Category | Amount (USD) |
|---|---|
| Servers (CPU + GPU) | 800,000 |
| InfiniBand network | 150,000 |
| Storage (BeeGFS + NVMe) | 200,000 |
| Rack, power, cooling | 80,000 |
| Installation and configuration | 60,000 |
| Total upfront cost | 1,290,000 |
| Annual maintenance and support | 80,000 |
| Annual power + space + cooling | 120,000 |
| 5-year TCO | 2,290,000 |
The Rental (OpEx) Model
HPC infrastructure is leased for a defined period; fixed monthly payments are made.
Rental Models
1. Hardware Leasing (Financial Lease): Standard finance lease with purchase option at end of term. Fixed monthly installments; you manage installation and operations. Typically 3–5 year terms.
2. Managed HPC Rental: Hardware, software, and operational management included. In Mevasis’s model, the cluster is ready for your team’s access; Mevasis handles administration.
3. On-Site Managed Lease: Hardware installed at your facility; ownership and management remain with the service provider. Preserves data sovereignty while transferring operational burden.
4. GPU Hours / CPU Hours (Pay-Per-Use): Consumption-based access. Ideal for low and variable utilization scenarios.
Advantages
- Low entry cost: No capital budget required
- Predictable spend: Fixed monthly cost simplifies budget forecasting
- Technology refresh: Upgrade to new generation at end of rental term
- Flexible scaling: Capacity expansion or contraction as needs evolve
- Operational transfer: Managed rental shifts HPC operations expertise to provider
Disadvantages
- Long-term cost: Continuing the same system beyond 7 years may exceed purchase cost
- Provider dependency: Service quality tied to provider performance
- Customization limits: Some rental models restrict hardware configuration changes
Example Rental Cost (Same Cluster, 5-Year Managed Rental)
| Category | Annual (USD) | 5-Year Total (USD) |
|---|---|---|
| Hardware rental installment | 280,000 | 1,400,000 |
| Management and operations (included) | — | — |
| Power + space + cooling | 120,000 | 600,000 |
| Total | 400,000/yr | 2,000,000 |
Note: Managed rental eliminates the HPC sysadmin headcount requirement. Staff cost savings are not reflected in the table but materially affect the comparison.
Comparative Analysis: 5-Year Scenarios
Scenario A: High Utilization (7,000+ Hours/Year)
| Model | 5-Year TCO | Notes |
|---|---|---|
| Purchase | $2,290,000 | Excludes staff cost |
| Managed rental | $2,000,000 | Operations included |
| Cloud (AWS p4d.24xlarge) | $4,200,000 |
Takeaway: At high utilization, purchase and managed rental are close; cloud is 2× more expensive.
Scenario B: Medium Utilization (3,000–5,000 Hours/Year)
| Model | 5-Year TCO |
|---|---|
| Purchase | $2,290,000 |
| Managed rental | $2,000,000 |
| Cloud | $2,100,000 |
Takeaway: All three models converge; rental and cloud offer flexibility, purchase provides control.
Scenario C: Low or Periodic Utilization (< 2,000 Hours/Year)
| Model | 5-Year TCO |
|---|---|
| Purchase | $2,290,000 |
| Managed rental | $2,000,000 |
| Cloud | < $1,000,000 |
| CPU/GPU Hours (Mevasis) | ~$500,000 |
Takeaway: At low utilization, cloud or hourly rental is clearly most economical.
Decision Framework
Annual usage < 2,000 hours?
→ Hourly rental or cloud
Usage > 5,000 hours AND capital budget available?
→ Purchase (lowest long-term TCO)
Usage > 5,000 hours BUT no capital budget?
→ Managed rental
Data sensitivity critical + no HPC staff?
→ On-site managed rental
Technology refresh speed is a priority?
→ Rental (3-year cycle)
Mevasis HPC Rental Services
Mevasis offers HPC rental solutions tailored to your organization’s requirements:
- On-site managed rental: Your facilities, maintenance and management from Mevasis
- CPU Hours and GPU Hours: Pay only for what you use
- Dedicated system rental: Non-shared, full-capacity access
- Short-term project rental: 3–12 month engagements
We conduct a complimentary needs analysis to determine the optimal model together.
Frequently Asked Questions
What is the difference between leasing and managed rental? Financial leasing includes a purchase option at end of term; operational/managed rental never transfers ownership. Cost structure and accounting treatment differ significantly.
What contract term is recommended? 3 years strikes a good balance for mid-scale deployments: technology refresh opportunity is preserved while unit cost is optimized. 5-year contracts typically offer lower monthly rates.
Can capacity be expanded during the rental term? Mevasis rental agreements include capacity expansion options as standard. Additional nodes are integrated into the existing system; expansion pricing is defined at contract signing.
Is HPC rental common? The model is growing, particularly among organizations with constrained capital budgets or those evaluating HPC before committing to ownership — universities, pharmaceutical companies, and engineering firms are primary adopters.