Why Choose Ollama?

Ollama is an excellent choice for developers who prioritize privacy and want complete control over their code analysis. With Ollama, all processing happens on your local machine, ensuring your code never leaves your computer. This is perfect for sensitive projects, air-gapped environments, or developers who simply prefer local processing.

Installing Ollama

Ollama is available for Windows, macOS, and Linux. Installation is straightforward:

  1. Visit ollama.com and download the installer for your platform
  2. Run the installer and follow the setup wizard
  3. Ollama will start automatically and run as a service

Once installed, Ollama runs in the background and is ready to use. You can verify it's running by opening a terminal and running ollama --version.

Installing Models

Ollama uses models that you download and run locally. Popular models for code analysis include:

  • llama3: General-purpose model, good balance of quality and speed
  • qwen2.5-coder: Specialized for code, excellent for code review
  • mistral: Fast and efficient, good for quick analysis
  • codellama: Code-specific model from Meta

To install a model, use the Ollama CLI:

ollama pull llama3
ollama pull qwen2.5-coder

You can browse available models at ollama.com/search to find models that suit your needs.

Configuring AI Diff Review

Once Ollama is installed and you have models available, configuring AI Diff Review is simple:

  1. Open Settings → Tools → AI Diff Review
  2. Select "Ollama (local)" as your provider
  3. Enter the Ollama host (default: http://localhost:11434)
  4. Click "Refresh" to load available models
  5. Select your preferred model from the dropdown

The plugin will test the connection and verify the model is available. Once configured, you're ready to start using Ollama for code analysis.

Using Ollama for Analysis

Using Ollama works exactly like cloud providers—just run an analysis through any of the normal entry points (Tools menu, context menus, VCS Log). The analysis happens locally, so you may notice:

  • Slightly slower processing (depending on your hardware)
  • No internet connection required
  • No API costs
  • Complete privacy

Hardware Requirements

Ollama's performance depends on your hardware:

CPU-Only

Ollama works on CPU-only systems, but analysis will be slower. Expect 30-60 seconds for typical analyses. This is fine for occasional use but may be too slow for frequent analysis.

GPU-Accelerated

If you have a compatible GPU (NVIDIA with CUDA, or Apple Silicon), Ollama can use it for much faster processing. GPU acceleration can make analysis 5-10x faster, making it practical for regular use.

Memory

Models require significant RAM. Smaller models (7B parameters) need ~8GB RAM, while larger models (13B+) may need 16GB or more. Check model requirements before installing.

Model Selection Tips

For Code Review

Code-specific models like qwen2.5-coder or codellama generally provide better analysis for code review tasks than general-purpose models.

For Speed

Smaller models like mistral or llama3:8b are faster but may provide less detailed analysis. Good for quick checks.

For Quality

Larger models like llama3:70b provide better analysis but require more resources and are slower. Use for important or complex changes.

Performance Optimization

Use GPU When Available

If you have a compatible GPU, Ollama will automatically use it. Make sure you have the appropriate drivers installed (NVIDIA drivers for CUDA, or use Apple's Metal on macOS).

Choose Appropriate Model Size

Don't use a 70B model if a 7B model is sufficient. Smaller models are faster and use less memory while still providing good analysis for most cases.

Monitor Resource Usage

Keep an eye on CPU, GPU, and memory usage. If Ollama is consuming too many resources, consider using a smaller model or adjusting when you run analyses.

Updating Models

Ollama models can be updated by pulling the latest version:

ollama pull llama3

This downloads the latest version if available. The plugin will continue using the model name you selected, so updates are seamless.

Troubleshooting

Connection Issues

If the plugin can't connect to Ollama:

  • Verify Ollama is running (ollama list should work)
  • Check the host address (default is http://localhost:11434)
  • Ensure no firewall is blocking the connection

Model Not Found

If your model doesn't appear in the list:

  • Verify the model is installed (ollama list)
  • Click "Refresh" in the plugin settings
  • Try pulling the model again if needed

Slow Performance

If analysis is too slow:

  • Try a smaller model
  • Enable GPU acceleration if available
  • Close other resource-intensive applications
  • Consider using cloud providers for time-sensitive analysis

Best Practices

Start with a Small Model

Begin with a 7B or 8B model to get a feel for performance. You can always switch to larger models if you need better analysis quality.

Keep Models Updated

Periodically update your models to get improvements and bug fixes. Newer versions often provide better analysis.

Use Appropriate Models for Tasks

Use code-specific models for code review, but don't hesitate to try general-purpose models if they work better for your specific use case.

Monitor Resource Usage

Keep an eye on system resources. If Ollama is impacting your development workflow, consider using it selectively or switching to cloud providers for some analyses.

Conclusion

Ollama provides an excellent option for local-first code review with AI Diff Review. By running analysis completely on your machine, you get complete privacy and control while avoiding API costs.

While local processing may be slower than cloud providers, the privacy and cost benefits make it an attractive option for many developers. With proper hardware and model selection, Ollama can provide fast, high-quality analysis that keeps your code completely private.

Whether you're working with sensitive code, prefer local processing, or want to avoid API costs, Ollama is a powerful tool that makes local AI code review practical and accessible.

Ready to try local analysis? Install AI Diff Review and set up Ollama for privacy-first code review.