Which AI Model Should You Use with GitHub Copilot?

Which AI model should I use with GitHub Copilot?

Choosing the right AI model for your GitHub Copilot project can be tricky. Each model has its own strengths, and understanding which one fits your needs best can make a big difference.

Whether you need speed, depth, or a balance of both, understanding what each model offers can help you make an informed decision. Let’s dive in. 👇

The TL;DR

• 💳 For a balance of cost and performance: GPT-4.1, GPT-4o, or Claude 3.5 Sonnet are solid choices.
• 🪙 For fast, lightweight tasks: o4-mini or Claude 3.5 Sonnet work well.
• 💎 For deep reasoning or complex debugging: Claude 3.7 Sonnet, o3, or GPT-4.5 are ideal.
• 🖼️ For multimodal inputs (like images): Gemini 2.0 Flash or GPT-4o are your go-to options.

These are general guidelines, but experimenting with different models can help you find the best fit for your specific needs.

🏎️ Prioritizing speed

o4-mini and o3-mini: The speed specialists 😈

If you need quick results without overcomplicating things, o4-mini and o3-mini are excellent options. They’re fast, efficient, and cost-effective.

✅ Best for:

• Rapid prototyping.
• Explaining small code snippets.
• Learning new programming concepts.
• Generating boilerplate code.

👀 Consider other models if: Your task involves multiple files or requires deep reasoning. In such cases, models like GPT-4.5 or o3 are better suited. For more expressive outputs, GPT-4o is a great alternative.

⚖️ Balanced AI models

Claude 3.5 Sonnet: The reliable all-rounder 😊

Claude 3.5 Sonnet strikes a balance between performance and cost, making it a dependable choice for everyday coding tasks.

✅ Best for:

• Writing documentation.
• Answering language-specific questions.
• Generating concise code snippets.

👀 Consider other models if: You need advanced reasoning or multi-step planning. For such tasks, Claude 3.7 Sonnet or GPT-4.5 are better options.

GPT-4o and GPT-4.1: The versatile performers 🌎

These models are highly flexible and can handle a wide range of tasks. Whether you need quick responses or support for text and images, they’ve got you covered.

✅ Best for:

• Explaining code blocks.
• Writing comments or documentation.
• Generating reusable code snippets.
• Handling multilingual prompts.

👀 Consider other models if: You’re tackling complex architectural reasoning or multi-step debugging. In such cases, GPT-4.5 or Claude 3.7 Sonnet are more effective.

🧠 Models for complex projects

Claude 3.7 Sonnet: The problem solver 🏠

Claude 3.7 Sonnet is designed for large, intricate projects. It excels in tasks that require deep context and detailed analysis.

✅ Best for:

• Refactoring large codebases.
• Planning complex system architectures.
• Designing algorithms.
• Combining high-level summaries with in-depth analysis.

👀 Consider other models if: You’re working on simpler tasks or need faster iterations. Claude 3.5 Sonnet or GPT-4o might be more efficient.

Gemini 2.5 Pro: The advanced researcher 🔎

Gemini 2.5 Pro is built for tackling challenging problems. It’s ideal for tasks that demand advanced reasoning and long-context capabilities.

✅ Best for:

• Writing full functions, classes, or multi-file logic.
• Debugging complex systems.
• Analyzing scientific data and generating insights.
• Processing extensive datasets or documents.

👀 Consider other models if: Budget is a concern. For cost-effective alternatives, try o4-mini or Gemini 2.0 Flash.

GPT-4.5: The deep thinker 💭

When you’re dealing with nuanced problems or need to design complex systems, GPT-4.5 is a strong choice.

✅ Best for:

• Writing detailed README files.
• Generating full functions or multi-file solutions.
• Debugging intricate errors.
• Making architectural decisions.

👀 Consider other models if: You’re working on smaller tasks or need faster results. GPT-4o is a quicker and more cost-effective option.

o3 and o1: The precision experts 🥽

For tasks that require logical precision and step-by-step problem-solving, o3 and o1 are excellent.

✅ Best for:

• Optimizing performance-critical code.
• Debugging complex systems.
• Writing structured, reusable code.
• Summarizing logs or benchmarks.

👀 Consider other models if: You’re in the early stages of prototyping or need something lightweight. o4-mini or GPT-4o might be better suited.

🖼️ Multimodal capabilities

Gemini 2.0 Flash: The visual problem-solver 🤔

If your work involves visual inputs like diagrams or UI mockups, Gemini 2.0 Flash is a great choice. It’s particularly useful for front-end development and layout debugging.

✅ Best for:

• Analyzing diagrams or screenshots.
• Debugging UI layouts.
• Generating code snippets.
• Providing design feedback.

👀 Consider other models if: Your task requires detailed algorithmic reasoning. GPT-4.5 or Claude 3.7 Sonnet are better equipped for such challenges.

Final thoughts

The key to choosing the right model is matching it to the task at hand. Over time, you’ll develop a sense of which models work best for different scenarios. Experimentation is the best way to learn and refine your approach.