Introduction

One of the most common questions businesses ask is:
“Should we use cloud AI or host our own LLM?”

This article breaks down the real cost, security, and performance differences between cloud AI and local deployment.

Cloud LLM Advantages

• No upfront hardware
• Fast setup
• Easy API integration
• Managed updates

Cloud LLM Disadvantages

• Monthly usage costs
• Vendor dependency
• Data privacy concerns
• Internet and latency dependency
• Compliance limitations

Local LLM Advantages

• One-time infrastructure investment
• No per-token billing
• Full data ownership
• Extreme low-latency
• Custom security and isolation

Local LLM Challenges

• Hardware investment
• Maintenance
• Cooling and power
• Monitoring and updates

Cost Comparison Example

• 10 users using AI daily
• 1 year of cloud API usage
• 1 private AI server purchase
• 3-year ownership comparison

Hybrid AI: The Best of Both Worlds

• Sensitive data handled locally
• Public AI only for low-risk workloads
• Intelligent routing between platforms

Final Thoughts

Cloud AI is great for testing.
Local AI is better for ownership, privacy, and long-term cost control.