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🤖 Models

Chaterm supports advanced code models from major providers, providing you with powerful AI programming assistant capabilities. Whether you're generating code, debugging, refactoring, or learning new technologies, you can find the perfect model for your needs.

✨ Built-in Models

Chaterm comes with multiple high-quality code models out of the box, ready to use without additional configuration:

🧠 Chain-of-Thought Models

These models have deep reasoning capabilities and can analyze problems step by step to provide detailed solutions:

ModelFeaturesUse Cases
DeepSeek-R1 (thinking)🎯 Advanced model with deep reasoning capabilitiesComplex algorithm design, architecture analysis
GLM-4.5 (thinking)🔍 Powerful logical reasoning capabilitiesCode review, problem diagnosis
DeepSeek-V3.1 (thinking)💡 Supports complex code analysisLarge project refactoring, performance optimization
Qwen-Plus (thinking)🚀 Alibaba Cloud's Tongyi Qianwen chain-of-thought modelMulti-language development, cross-platform projects

⚡ Standard Models

Fast-response standard models suitable for daily programming tasks:

ModelFeaturesUse Cases
GLM-4.5🎨 Excellent code generation capabilitiesRapid prototyping, feature implementation
Qwen-Plus🏆 High-performance code generation modelEnterprise application development
Qwen-Turbo⚡ Fast-response lightweight modelReal-time programming assistance, rapid iteration

🔧 Model Selection Recommendations

When to Use Chain-of-Thought Models

  • 🔍 Need deep analysis of complex problems
  • 🏗️ Design system architecture
  • 🐛 Debug complex errors
  • 📚 Learn new technology concepts

When to Use Standard Models

  • ⚡ Quick command generation
  • 🔄 Daily operations tasks
  • 📝 Code comments and documentation
  • 🛠️ Simple refactoring

⚙️ Add Custom Models

You can add more model providers in settings to extend Chaterm's functionality:

💡 Usage Tips

Model Switching

  • Choose the appropriate model based on task type
  • Chain-of-thought models are suitable for complex tasks, standard models for rapid development

Best Practices

  • 🎯 Clearly describe your requirements
  • 📝 Provide sufficient context information
  • 🔄 Try different models to get the best results
  • 💬 Engage in multi-turn conversations with models to refine solutions