AI is transforming coding like never before. I think we have all seen that ChatGPT code meme.

AI coding tools can be useful to suggest code, detect errors, and even generate entire snippets, giving developers more time to focus on creative problem-solving and building innovative solutions.

Just last year, GitHub announced their free tier for GitHub Copilot to make coding with AI more accessible to developers. Note that students, educators, and open source maintainers already have free access to unlimited Copilot Pro.

This makes me wonder if there are other free coding AI alternatives out there and how do they fare in comparison to GitHub’s Copilot. In today’s article, let’s dive into 3 AI coding tools: Qodo, Codeium, and GitHub Copilot. We’ll break down their features, strengths, and weaknesses to help you choose the one that fits your needs best.

1. Qodo

Qodo (formerly Codium) represents a newer entrant in the AI coding assistant space, focusing on providing intelligent code completions and suggestions. Its key features include:

• Real-time code analysis and suggestions

• Support for multiple programming languages including Python, JavaScript, and Java

• Integration with popular IDEs like VS Code and JetBrains products

• Emphasis on privacy and data security with local processing options

• Limitations in free tier

2. Codeium

Codeium has positioned itself as a powerful alternative in the AI coding assistant market, offering:

• Advanced code completion capabilities with AI chat function

• Supports over 70 languages with context-aware suggestions

• Built-in code explanation and documentation features

• Seamless IDE integration across multiple platforms

• Free-tier availability for individual developers offers many excellent features

3. GitHub Copilot

As an industry leader in AI pair programming, GitHub Copilot offers:

• Deep integration with the GitHub ecosystem

• Advanced code generation capabilities by powerful LLMs (GPT-4o and Claude 3.5 Sonnet)

• Extensive language and framework support

• Context-aware code suggestions

• Built-in security scanning and best practices recommendations

• Limits in free tier

Performance Comparison

Accuracy and Quality of code suggestions

Below is the result of my prompt to write a function that validates whether a string is an email in Python. Note: For this test, I only use their IDE products, not their chat, slash commands or other products.

# GitHub Copilot suggestion (✅ Minimal modification needed)
def validate_email(email):
    import re
    pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
    return bool(re.match(pattern, email))

# Codeium suggestion (✅ Minimal modification needed)
def is_valid_email(email):
    """
    Validate if a string is an email

    :param email: The string to validate
    :return: True if the string is a valid email, False otherwise
    """
    import re
    regex = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
    return re.match(regex, email) is not None

# Qodo suggestion (suggested code improvements)
def validate_email(email: str) -> bool:
    """
    Validates if the provided email string matches a basic email pattern.

    Args:
    email (str): The email address to validate.

    Returns:
    bool: True if the email matches the pattern, False otherwise.
    """
    pattern = r'^[\w\.-]+@[\w\.-]+\.\w+$' 
    return bool(re.match(pattern, email))

Speed and Efficiency

Below are some tests performed to compare each tool’s speed and efficiency. Note: Results may differ depending on many factors like the hardware you are using, internet speed and other environmental conditions.

Basic Code Completion

Average response time (in milliseconds):

• GitHub Copilot: 127ms

• Codeium: 156ms

• Qodo: N/A (only code improvement suggestions)

Key Observation: While Copilot led in raw speed, all tools performed within acceptable latency ranges (<200ms) for maintaining flow state during coding.

Full Function Generation/Improvement

Average time to generate a complete function (in seconds):

Test Case: REST API endpoint handler with authentication

• GitHub Copilot: 1.2s

• Codeium: 1.8s

• Qodo: 2.1s

Test Case: Data processing utility function (500 lines)

• GitHub Copilot: 2.4s

• Codeium: 3.1s

• Qodo: 3.3s

Usability and User Experience

• All three tools offer VS Code integration and support with various popular IDEs, but GitHub Copilot seamlessly integrates with GitHub Codespaces and GitHub ecosystems

• All offer very quick and easy experience to install the plugin and use in code editors

Qodo

Upon installing Qodo’s IDE plugin, you will have to authorize it with your GitHub.

Back in your code editor, you can open Qodo’s chat window. They have slash commands which allows you to generate tests, explain or improve your code.

Their free tier does not include autocompletion of code unlike Codeium and Copilot. However, you can easily generate code to improve your existing ones within the IDE itself. But the experience was not as quite smooth because it takes a few clicks to finally get the code output:

1. First click the ‘Qodo Gen: Options’

2. Dropdown menu appears. Click ‘/enhance’ to open the chat panel

3. Click ‘Send’ icon to execute the slash command in chat

4. Click ‘Show Diff’ to get the code suggestion.

Also, when giving multiple code suggestions, I had to preview them one by one, unlike in Copilot where I can see the code directly. This makes the user experience slightly not ideal.

I think what Qodo excels most at is generating tests. It is easily to click the ‘Test this function’ in the IDE and the test suites generated has a lot of details, coverage and customizability, which makes testing a seamless process in the workflow.

Codeium

When you first install Codeium, you will be redirected to a page to create an account.

Codeium offers keyboard shortcuts and shows them explicitly so you can use them immediately. The interface is minimalistic and simple to use.

It allows you to refactor, explain its code from its chat panel and generate docstring with just a click. its chat functions also can perform use tasks like generating tests.

While I was testing a few code generations, I did encounter a “context exceeded” error from the plugin. It stops autocompleting my code after I saw the error but still generates code if I explicitly command it. I realized this has been an ongoing issue.

GitHub Copilot

When you first sign up for Copilot, you are allowed to opt out from data collection for AI training, or other privacy conerns.

I love the inline-chat UI and how easy it is to prompt for function generation, re-generate the code and perform other actions. Cycling through suggestions through a side panel is also easy and intuitive to use.

The extension also includes options to review and modify your code with Copilot when you highlight it.

Pricing and Accessibility

Qodo

Qodo’s free tier includes:

• AI code review & suggestions

• Bug detection and fixing

• Code auto-documentation

• Direct chat with GPT-4o

• and more

However, some great features are only available behind a paywall:

• Code autocomplete

• Coding Agent (advanced task-aware code completion)

• And more

See its paid tier and pricing plans here.

Codeium

Codeium’s free tier has pretty solid offerings:

• Access to the Windsurf Editor (their in-house AI IDE)

• Access to all Codeium Extensions

• Unlimited AI autocomplete

• Unlimited in-editor AI chats

• Unlimited AI command instructions

But additional features would be paid, which you can check out on this page.

GitHub Copilot

GitHub Copilot Free Tier offers 2000 code completions/month. Other features include a chat option with 50 free chat requests per month, providing access to both the GPT-4o and Claude 3.5 Sonnet models.

More on its paid tier and pricing plans here.

Summary

Conclusion

The choice between these AI tools ultimately depends on specific needs, budget constraints, and development workflows. While GitHub Copilot has established itself as a market leader, both Qodo and Codeium offer compelling alternatives with unique strengths. Consider factors such as:

• Your primary programming languages and frameworks

• Integration requirements with existing tools

• Budget constraints and team size

• Privacy and security requirements

• Specific feature needs for your development workflow

Furthermore, with how quickly AI is evolving, it wouldn't be far-fetched to see new features added to all these tools to give them a competitive edge. When that time comes, this article might become outdated.

Thanks for reading! As always, I hope you find this article helpful! Feel free to like, comment and share! Let me know your experience if you have used these tools before! See you in the next article! Cheers!

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References

• https://www.qodo.ai/

• https://codeium.com/vscode_tutorial

• https://code.visualstudio.com/blogs/2024/12/18/free-github-copilot

• https://docs.github.com/en/copilot/about-github-copilot/subscription-plans-for-github-copilot