For teams considering on-prem AI hardware, the rent-vs-buy math is more nuanced than just "capital cost / monthly rental". Power, cooling, refresh, depreciation, and operational overhead all matter.
For an RTX 5090 server: buyout pays back in ~18 months if you absorb the operational cost. Rental wins if you don't already have datacenter / 24/7 ops capacity. For most teams not already running infrastructure, rental wins for the first 2 years.
What buyout actually costs
RTX 5090 server build:
- RTX 5090: ~£2,000
- Workstation chassis + PSU: ~£800
- Threadripper + 64 GB ECC + 2 TB NVMe: ~£2,500
- Hardware total: ~£5,300
- + Power (575 W × 24/7 × £0.20/kWh): ~£100/mo
- + Cooling / rack space: ~£50-200/mo
- + Network: ~£50/mo
- + Operational overhead (1 hour/week × £50/hr): ~£200/mo
- + Depreciation over 3 years: ~£150/mo
- True monthly cost: ~£550-700/mo
What rental actually costs
RTX 5090 dedicated at GigaGPU: £399/mo all-in. Includes hardware, power, cooling, network, datacenter operations, replacement-on-failure.
Break-even horizon
Buyout fixed cost: £5,300. Monthly rental: £359. Naive break-even: ~15 months.
But: rental includes operations. Buyout adds £200-400/mo of real operational + power cost. Real break-even: ~24-30 months.
Verdict
- You already operate datacenter/colocation: buyout pays back in ~18 months
- You don't have datacenter ops: rental wins for ~3 years
- You need flexibility: rental — swap GPUs as new generations land
- Rapid AI evolution: rental — depreciation on consumer GPU is steep
Bottom line
For most AI startups and SaaS companies, rental wins for the first 2-3 years. After that, if your workload is stable, buyout becomes meaningful. See serverless vs dedicated.
