Choosing an AI Model for Fix Prompts (Advanced)
Different AI models have different strengths for code fixes. GPT-4 excels at complex reasoning, Claude is great for following instructions, and smaller models are faster but less capable. Choose based on code complexity, model capabilities, and your needs.
Model Options
GPT-4 (OpenAI)
Best for: Complex bugs, multi-file issues, architectural problems
- Strengths: Excellent reasoning, understands context well, good at complex problems
- Weaknesses: Slower, more expensive, may be overkill for simple issues
- When to use: Complex bugs, multi-file fixes, architectural issues
Claude (Anthropic)
Best for: Following detailed instructions, long codebases, precise fixes
- Strengths: Great at following instructions, handles long context, precise fixes
- Weaknesses: May be slower, less creative than GPT-4
- When to use: When you need precise fixes, complex instructions
GPT-3.5 (OpenAI)
Best for: Simple bugs, quick fixes, cost-effective solutions
- Strengths: Fast, cheap, good for simple issues
- Weaknesses: Less capable, may struggle with complex problems
- When to use: Simple bugs, straightforward fixes, when speed/cost matters
Local Models (Ollama, etc.)
Best for: Privacy-sensitive code, offline use, experimentation
- Strengths: Privacy, no API costs, works offline
- Weaknesses: Less capable, requires setup, slower
- When to use: Sensitive code, when you need privacy
Choosing Based on Issue Complexity
Simple Issues
For simple bugs (typos, syntax errors, obvious fixes):
- Recommended: GPT-3.5 or Claude Haiku
- Why: Fast, cheap, capable enough for simple fixes
- Example: Missing semicolon, typo in variable name
Moderate Issues
For moderate bugs (logic errors, single-file fixes):
- Recommended: GPT-4 or Claude Sonnet
- Why: Better reasoning, understands context better
- Example: Incorrect conditional logic, wrong function call
Complex Issues
For complex bugs (multi-file, architectural, business logic):
- Recommended: GPT-4 or Claude Opus
- Why: Best reasoning, handles complex context
- Example: Refactoring needed, multi-file changes
Choosing Based on Your Needs
Speed vs Quality
- Fast but less accurate: GPT-3.5, Claude Haiku
- Balanced: Claude Sonnet, GPT-4 Turbo
- Slower but more accurate: GPT-4, Claude Opus
Cost Considerations
- Budget-friendly: GPT-3.5, Claude Haiku
- Moderate cost: Claude Sonnet, GPT-4 Turbo
- Higher cost: GPT-4, Claude Opus
Privacy Requirements
- API models: Code sent to external services
- Local models: Code stays on your machine
- Consider: Sensitive code, company policies
Best Practices
- Start simple - Try GPT-3.5 first, upgrade if needed
- Use right tool for job - Don't use GPT-4 for simple fixes
- Experiment - Try different models to see what works
- Consider cost - Balance quality vs cost for your needs
- Review always - Regardless of model, always review suggestions
Model Comparison
| Model | Speed | Quality | Cost | Best For |
|---|---|---|---|---|
| GPT-3.5 | Fast | Good | Low | Simple fixes |
| GPT-4 | Slow | Excellent | High | Complex issues |
| Claude Haiku | Fast | Good | Low | Simple fixes |
| Claude Opus | Slow | Excellent | High | Complex issues |
Default Recommendations
- Most users: Start with GPT-4 or Claude Sonnet (good balance)
- Simple bugs: Use GPT-3.5 or Claude Haiku (faster, cheaper)
- Complex issues: Use GPT-4 or Claude Opus (better quality)
- Privacy-sensitive: Use local models or on-premise solutions