The biggest mistake: looking only at the API price.
1. Cost Components
- API
- server
- GPU/CPU
- bandwidth
- maintenance
2. Comparison
Numeric Example #1
| Model | Cost |
|---|---|
| API | $50–300 |
| VPS | $30–100 |
| GPU | $400–1500 |
3. Hidden Costs
- scaling
- maintenance
- performance
4. Per-User Cost
Numeric Example #2
| Users | Cost |
|---|---|
| 100 | $50 |
| 1,000 | $300 |
| 10,000 | $2,000+ |
5. Scenario
BEFORE:
- $80
AFTER:
- $1,050
6. Benchmark
| System | Cost | Perf |
|---|---|---|
| API | medium | good |
| VPS | low | poor |
| GPU | high | good |
7. Calculation
total = api + server + bandwidth + maintenancecost = users * per_user8. Reality vs Hype
Hype:
- cheap
Reality:
- gets expensive as you scale
9. Risks
- cost escalation
- ROI decline
10. Trade-off
| Model | Pro | Con |
|---|---|---|
| API | fast | expensive |
| VPS | cheap | weak |
| GPU | powerful | expensive |
11. External Sources
- OpenAI Pricing
- AWS GPU Pricing
12. Internal Links
- /blog/ai-hosting-secimi
- /blog/vps-vs-dedicated-performans-analizi
- /blog/ai-performans-etkisi
13. Conclusion (CTA)
AI costs are different from what you think.
Submit a request for an analysis.
SELF_CHECK:
intentmatch: yes numericcount: 3 metriccount: 5 implementationcount: 2 sourcescount: 2 benchmarkcontext: provided comparison_strength: strong