Comparison of AI models for GitHub Copilot
GitHub Copilot supports multiple AI models with different capabilities. The model you choose affects the quality and relevance of responses by Copilot Chat and Copilot code completion. Some models offer lower latency, while others offer fewer hallucinations or better performance on specific tasks. This guide helps you pick the best model based on your task, not just model names.
Note
- Different models have different premium request multipliers, which can affect how much of your monthly usage allowance is consumed. For details, see Requests in GitHub Copilot.
- When you use Copilot Chat in VS Code, it automatically selects the best model for you based on availability. You can manually choose a different model to override this selection. See About Copilot auto model selection and Changing the AI model for GitHub Copilot Chat.
Recommended models by task
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Use this table to find a suitable model quickly, see more detail in the sections below.
| Model | Task area | Excels at (primary use case) | Additional capabilities | Further reading |
|---|---|---|---|---|
| GPT-4.1 | General-purpose coding and writing | Fast, accurate code completions and explanations | Agent mode, vision | GPT-4.1 model card |
| GPT-5-Codex | General-purpose coding and writing | Fast, accurate code completions and explanations | Agent mode | GPT-5-Codex model card |
| GPT-5 mini | General-purpose coding and writing | Fast, accurate code completions and explanations | Agent mode, reasoning, vision | GPT-5 mini model card |
| GPT-5 | Deep reasoning and debugging | Multi-step problem solving and architecture-level code analysis | Reasoning | GPT-5 model card |
| Claude Haiku 4.5 | Fast help with simple or repetitive tasks | Fast, reliable answers to lightweight coding questions | Agent mode | Not available |
| Claude Sonnet 4.5 | General-purpose coding and agent tasks | Complex problem-solving challenges, sophisticated reasoning | Agent mode | Claude Sonnet 4.5 model card |
| Claude Opus 4.1 | Deep reasoning and debugging | Complex problem-solving challenges, sophisticated reasoning | Reasoning, vision | Claude Opus 4.1 model card |
| Claude Sonnet 3.5 | Fast help with simple or repetitive tasks | Quick responses for code, syntax, and documentation | Agent mode, vision | Claude Sonnet 3.5 model card |
| Claude Sonnet 4 | Deep reasoning and debugging | Performance and practicality, perfectly balanced for coding workflows | Agent mode, vision | Claude Sonnet 4 model card |
| Gemini 2.5 Pro | Deep reasoning and debugging | Complex code generation, debugging, and research workflows | Reasoning, vision | Gemini 2.5 Pro model card |
| Grok Code Fast 1 | General-purpose coding and writing | Fast, accurate code completions and explanations | Agent mode | Grok Code Fast 1 model card |
| Qwen2.5 | General-purpose coding and writing | Code generation, reasoning, and code repair / debugging | Reasoning | Qwen2.5 model card |
Task: General-purpose coding and writing
Use these models for common development tasks that require a balance of quality, speed, and cost efficiency. These models are a good default when you don't have specific requirements.
| Model | Why it's a good fit |
|---|---|
| GPT-5-Codex | Delivers higher-quality code on complex engineering tasks like features, tests, debugging, refactors, and reviews without lengthy instructions. |
| GPT-5 mini | Reliable default for most coding and writing tasks. Fast, accurate, and works well across languages and frameworks. |
| Grok Code Fast 1 | Specialized for coding tasks. Performs well on code generation, and debugging across multiple languages. |
When to use these models
Use one of these models if you want to:
- Write or review functions, short files, or code diffs.
- Generate documentation, comments, or summaries.
- Explain errors or unexpected behavior quickly.
- Work in a non-English programming environment.
When to use a different model
If you're working on complex refactoring, architectural decisions, or multi-step logic, consider a model from Deep reasoning and debugging. For faster, simpler tasks like repetitive edits or one-off code suggestions, see Fast help with simple or repetitive tasks.
Task: Fast help with simple or repetitive tasks
These models are optimized for speed and responsiveness. They’re ideal for quick edits, utility functions, syntax help, and lightweight prototyping. You’ll get fast answers without waiting for unnecessary depth or long reasoning chains.
Recommended models
| Model | Why it's a good fit |
|---|---|
| Claude Haiku 4.5 | Balances fast responses with quality output. Ideal for small tasks and lightweight code explanations. |
| Claude Sonnet 3.5 | Balances fast responses with quality output. Ideal for small tasks and lightweight code explanations. |
When to use these models
Use one of these models if you want to:
- Write or edit small functions or utility code.
- Ask quick syntax or language questions.
- Prototype ideas with minimal setup.
- Get fast feedback on simple prompts or edits.
When to use a different model
If you’re working on complex refactoring, architectural decisions, or multi-step logic, see Deep reasoning and debugging. For tasks that need stronger general-purpose reasoning or more structured output, see General-purpose coding and writing.
Task: Deep reasoning and debugging
These models are designed for tasks that require step-by-step reasoning, complex decision-making, or high-context awareness. They work well when you need structured analysis, thoughtful code generation, or multi-file understanding.
Recommended models
| Model | Why it's a good fit |
|---|---|
| GPT-5 mini | Delivers deep reasoning and debugging with faster responses and lower resource usage than GPT-5. Ideal for interactive sessions and step-by-step code analysis. |
| GPT-5 | Great at complex reasoning, code analysis, and technical decision-making. |
| Claude Sonnet 4 | Improves on 3.7 with more reliable completions and smarter reasoning under pressure. |
| Claude Opus 4.1 | Anthropic’s most powerful model. Improves on Claude Opus 4. |
| Gemini 2.5 Pro | Advanced reasoning across long contexts and scientific or technical analysis. |
When to use these models
Use one of these models if you want to:
- Debug complex issues with context across multiple files.
- Refactor large or interconnected codebases.
- Plan features or architecture across layers.
- Weigh trade-offs between libraries, patterns, or workflows.
- Analyze logs, performance data, or system behavior.
When to use a different model
For fast iteration or lightweight tasks, see Fast help with simple or repetitive tasks. For general development workflows or content generation, see General-purpose coding and writing.
Task: Working with visuals (diagrams, screenshots)
Use these models when you want to ask questions about screenshots, diagrams, UI components, or other visual input. These models support multimodal input and are well suited for front-end work or visual debugging.
| Model | Why it's a good fit |
|---|---|
| GPT-5 mini | Reliable default for most coding and writing tasks. Fast, accurate, and supports multimodal input for visual reasoning tasks. Works well across languages and frameworks. |
| Claude Sonnet 4 | Improves on 3.7 with more reliable completions and smarter reasoning under pressure. |
| Gemini 2.5 Pro | Deep reasoning and debugging, ideal for complex code generation, debugging, and research workflows. |
When to use these models
Use one of these models if you want to:
- Ask questions about diagrams, screenshots, or UI components.
- Get feedback on visual drafts or workflows.
- Understand front-end behavior from visual context.
Tip
If you're using a model in a context that doesn’t support image input (like a code editor), you won’t see visual reasoning benefits. You may be able to use an MCP server to get access to visual input indirectly. See Extending GitHub Copilot Chat with Model Context Protocol (MCP) servers.
When to use a different model
If your task involves deep reasoning or large-scale refactoring, consider a model from Deep reasoning and debugging. For text-only tasks or simpler code edits, see Fast help with simple or repetitive tasks.
Next steps
Choosing the right model helps you get the most out of Copilot. If you're not sure which model to use, start with a general-purpose option like GPT-4.1, then adjust based on your needs.
- For detailed model specs and pricing, see Supported AI models in GitHub Copilot.
- For more examples of how to use different models, see Comparing AI models using different tasks.
- To switch between models, refer to Changing the AI model for GitHub Copilot Chat or Changing the AI model for GitHub Copilot code completion.
- To learn how Copilot Chat serves different AI models, see Hosting of models for GitHub Copilot Chat.