VPS vs Dedicated Machine: Where to Run OpenClaw
VPS vs Dedicated Machine: Where to Run OpenClaw
One of the first questions newcomers ask: where should I run OpenClaw? Here's a comparison to help you decide.
Hosting Options
| Option | Cost | Best For |
|---|---|---|
| VPS | ~$20/month | Testing, getting started |
| Mini PC | ~$200 one-time | Long-term, serious use |
| Raspberry Pi | ~$100 | DIY, limited budget |
| Old Laptop | $0 | Using what you have |
VPS: Pros and Cons
Pros:
- Quick start
- No hardware hassle
- Access from anywhere
- Low entry barrier
Cons:
- Monthly payments
- Data not with you
- Provider dependency
- Cancel = everything gone
Recommended providers:
- Hetzner (~$5-20/month)
- DigitalOcean (~$10-20/month)
- Vultr (~$10-20/month)
Dedicated Machine: Pros and Cons
Pros:
- One-time payment
- Full control
- Data stays local
- Pays for itself in 10 months
Cons:
- Initial investment
- Setup required
- Need home internet
- Electricity costs
Recommended hardware:
- Mini PC (N97, 16GB RAM) — ~$200
- Mac Mini (M1) — ~$500+
- Intel NUC — ~$300+
ROI Calculation
VPS $20/month × 12 = $240/year
Mini PC $200 + electricity ~$30/year = $230 first year
Result: Dedicated pays for itself in about a year.
Security
VPS: Data on other people's servers, need VPN
Local: Data at home, use Tailscale for remote access
Recommendations
Beginners: VPS for 1-3 months testing
Serious use: Dedicated Mini PC
DIY enthusiasts: Raspberry Pi 5
Business: Mini PC + backup VPS
Start with VPS, graduate to dedicated.
👀 See Also
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Custom Command Center App for OpenClaw: React PWA with WebSocket Proxy and Tailscale
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OpenClaw Failure Patterns: 42 Real Incidents in 28 Days
A developer running OpenClaw daily documented 42 specific failures across eight categories, including AI hallucinations, authentication breakdowns, and automation that costs more time than it saves. The source provides concrete examples like Google OAuth 7-day token expiration and Opus 4.6 adding unwanted metadata to files.
Export ChatGPT history to OpenClaw memory system
A Reddit user shares a process to export years of ChatGPT conversation history and import it into OpenClaw's memory system using the ai-chat-md-export tool, enabling local AI agents to access historical context.