Cloud: Scalable, no upfront cost, pay-per-use ($0.28-6/hr), instant access to latest GPUs (H100, A100), scales from 1 to 100+ GPUs in minutes. Local: One-time cost ($2-40K/GPU), full control, faster data access, power/cooling costs (~$0.15/kWh), 3-5 year depreciation. Cloud is better for experiments, variable workloads, and teams. Local is better for 24/7 production, data sovereignty, and >12-18 month continuous usage.
Cost Comparison: Cloud vs Local
| Metric | Cloud GPU (io.net) | Local GPU (Own Hardware) |
|---|---|---|
| Upfront cost | $0 | $2,000-40,000 per GPU |
| Hourly rate | $0.28-6/hr (pay-per-second) | $0.15-0.30/hr (electricity only) |
| Maintenance | Included | $200-500/year per GPU |
| Scaling | 1 to 100+ GPUs in minutes | Weeks/months to procure+install |
| Hardware refresh | Always latest (H100, A100) | 3-5 year depreciation cycle |
When Cloud Makes Sense
- Sporadic usage: <16 hours/day or bursty workloads
- Rapid experimentation: Test 10+ model architectures, hyperparameter sweeps
- Variable demand: Spike from 1 to 50 GPUs for deadlines
- Short-term projects: 3-6 month research initiatives
- Team collaboration: Multiple users sharing GPU pool
When Local Makes Sense
- 24/7 production: Continuous inference serving, training pipelines
- Data sovereignty: Regulated data that cannot leave premises
- 12+ month usage: Break-even point where capex is cheaper than cloud opex
- Ultra-low latency: <1ms response times (no network overhead)
Break-Even Analysis
Example: A100 80GB GPU
- Local cost: $15,000 (hardware) + $1,000 (PSU/cooling) + $500/yr (power @ 300W, 24/7)
- Cloud cost: $2/hr × 720 hrs/month = $1,440/month
- Break-even: $16,000 ÷ $1,440 = 11 months of 24/7 usage
If you use the GPU <16 hours/day, cloud is always cheaper. If you use it 24/7 for >12 months, local becomes cost-effective.
Hybrid approach: Many companies use cloud for experimentation (70% of GPU time) and local for production inference (30%). This balances flexibility with cost efficiency.
Start today, Scale When Ready
Test your workload on io.net cloud GPUs risk-free. Migrate to local infrastructure only when usage justifies the capex.
