Self-Host Llama 2 on DigitalOcean for $5/Month

Description and use

Successfully deployed a private Llama 2 inference server on a $5/month VPS, reducing costs from ~$847/month (for comparable GPT-4 usage) to $5/month, with full control over data and no rate limits.

Problem

High costs associated with proprietary AI APIs (e.g., GPT-4) for side projects, lack of privacy, rate limits, and terms of service restrictions on fine-tuning.

Outcome

Successfully deployed a private Llama 2 inference server on a $5/month VPS, reducing costs from ~$847/month (for comparable GPT-4 usage) to $5/month, with full control over data and no rate limits.

Workflow

• Create a $5/month DigitalOcean Droplet with Ubuntu 22.04 x64.
• SSH into the Droplet and update the system packages.
• Install Ollama using the official installation script.
• Enable and start the Ollama systemd service.
• Download the Llama 2 7B model using 'ollama pull llama2:7b'.
• Test local inference using 'ollama run llama2:7b'.
• Configure Ollama to listen on all interfaces (0.0.0.0) by editing the systemd service environment.
• Restart Ollama and verify it is listening on port 11434.
• Test the API endpoint from a local machine using curl.

Evidence

Last month, I calculated the cost of running GPT-4 API calls for a side project: $847. The same workload on a self-hosted Llama 2 instance? $5/month.

Source

I've tested every command on fresh Ubuntu 22.04 instances. Nothing theoretical here—this is what actually works.

Source