Understanding Your Options

AI Diff Review supports both local and cloud AI providers, giving you flexibility to choose based on your privacy requirements, performance needs, and budget. Understanding the differences between these options will help you make the best choice for your development workflow.

Local Providers: Privacy and Control

Ollama

Ollama is a popular choice for developers who want complete privacy and control over their code analysis. With Ollama, all processing happens on your local machine, ensuring your code never leaves your computer.

Advantages:

  • Complete privacy - code never leaves your machine
  • No API costs - free to use
  • Works offline - no internet connection required
  • Full control over models and versions
  • No rate limits or usage restrictions

Considerations:

  • Requires sufficient local hardware (CPU/GPU)
  • Model download and storage space needed
  • May be slower than cloud providers for large analyses
  • You're responsible for model updates

Best for: Developers working with sensitive code, air-gapped environments, or those who prefer complete control over their AI infrastructure.

LM Studio

LM Studio provides an OpenAI-compatible API that runs locally, giving you the flexibility of a cloud-like interface with the privacy of local processing.

Advantages:

  • OpenAI-compatible API makes it easy to switch between local and cloud
  • User-friendly interface for model management
  • Supports many popular models
  • Complete privacy like Ollama

Considerations:

  • Similar hardware requirements to Ollama
  • Requires LM Studio application to be running
  • Default port configuration needed

Best for: Developers who want local processing but prefer a managed interface for model handling.

Cloud Providers: Power and Convenience

OpenAI

OpenAI's GPT-5 and GPT-5-mini models offer powerful analysis capabilities with fast response times. The "Think harder" mode uses GPT-5 for more thorough analysis when needed.

Advantages:

  • Excellent analysis quality and accuracy
  • Fast response times
  • No local hardware requirements
  • Regular model updates and improvements
  • Reliable infrastructure

Considerations:

  • API costs per request
  • Code sent to external service (though secret redaction helps)
  • Requires internet connection
  • Subject to rate limits

Best for: Teams that prioritize analysis quality and speed, have budget for API costs, and are comfortable with cloud processing.

Claude (Anthropic)

Claude offers strong reasoning capabilities, with Claude Opus providing deep analysis in "Think harder" mode and Claude Sonnet offering a good balance of speed and quality.

Advantages:

  • Strong reasoning and context understanding
  • Good security analysis capabilities
  • Reliable performance
  • Competitive pricing

Best for: Teams needing deep analysis, especially for security-focused code reviews.

Gemini (Google)

Google's Gemini models provide excellent performance with competitive pricing. Gemini 2.5 Pro offers comprehensive analysis, while Flash provides faster responses.

Advantages:

  • Competitive pricing
  • Good analysis quality
  • Fast response times with Flash
  • Integration with Google ecosystem

Best for: Teams already using Google services or looking for cost-effective cloud analysis.

Grok (xAI)

xAI's Grok models offer a modern alternative with strong capabilities. Grok-4-latest provides comprehensive analysis, while the fast variant offers quick responses.

Advantages:

  • Modern architecture
  • Good performance
  • Competitive features

Best for: Teams wanting to explore newer AI options or diversify their AI provider usage.

Making the Right Choice

Choose Local If:

  • You work with highly sensitive or proprietary code
  • You're in an air-gapped or restricted network environment
  • You want to avoid API costs
  • You have sufficient local hardware
  • You prefer complete control over your AI infrastructure

Choose Cloud If:

  • You prioritize analysis quality and speed
  • You have budget for API costs
  • You don't have powerful local hardware
  • You want the latest model improvements automatically
  • You're comfortable with code being processed externally (with secret redaction)

Hybrid Approach

You're not limited to a single provider. Many teams use a hybrid approach:

  • Use local providers (Ollama/LM Studio) for sensitive projects
  • Use cloud providers for less sensitive code or when you need faster analysis
  • Switch between providers based on the specific needs of each project

AI Diff Review makes it easy to switch between providers in the settings, so you can adapt your workflow as needed.

Conclusion

The choice between local and cloud providers depends on your specific needs, privacy requirements, and resources. Local providers offer complete privacy and control, while cloud providers provide powerful analysis with minimal setup. Many developers find value in having both options available, using each where it makes the most sense.

Remember, you can always change your provider in the settings, so don't feel locked into your initial choice. Experiment with different options to find what works best for your workflow.

Ready to choose your provider? Install AI Diff Review and start exploring the options available to you.