ChatGPT vs Bard: Which is better for coding?

Introduction Of ChatGPT

For programmers, generative AI offers substantial benefits. It helps with writing and debugging code, making our lives a little easier. But with competing tools like ChatGPT and Bard, the question arises: which one is the best for me?


This article compares these AI tools to determine which is the most feature-rich for programming purposes.

ChatGPT and Bard: What’s the Difference?

The core difference lies in the Large Language Models (LLMs) powering each tool. It utilizes GPT-4, while Bard is powered by LaMDA. Additionally, It is developed by OpenAI, and Bard was created by Google.

In terms of functionalities, they offer similar capabilities:

  • Suggestions: Both can recommend proper syntax and parameters for functions and other code constructs.
  • Completion: They can complete code you’ve started writing.
  • Debugging: They can help identify errors and issues in your code.
  • Explanation: They can explain the code they generate or code you provide.

Both models were trained on massive datasets, including code repositories, web documents, and scraped content. However, Bard received training on conversations and dialogues, while ChatGPT focused on scraped general content.

Both products are under development, with Bard being a little less mature. To understand the practical implications of these differences, let’s see how they perform in specific tests.

Testing ChatGPT and Bard

We evaluated them across seven categories relevant to programmers: code generation, problem-solving, code refactoring, debugging assistance, third-party plugins/UI extensions, ease of use, and cost.

1. Code Generation

We asked them to write a Python function that returns a list of 100 prime numbers.

Winner: ChatGPT

Both produced functional results, but It code was cleaner and more efficient. It also interpreted the vague prompt correctly. However, remember that chatbot responses can vary depending on the programming language and complexity of the query.

2. Problem Solving

We presented a LeetCode problem requiring them to enhance arrays with a last() method to return the last element.

Winner: ChatGPT (with reservations)

While both produced nearly identical solutions, It offered a clearer explanation of the code’s functionality. This is valuable for learning how to solve problems independently.

3. Code Refactoring

We challenged them to optimize a provided code snippet.

Winner: Bard

Bard excelled in refactoring. It not only provided optimized code but also demonstrated benchmark creation and results, showcasing a more comprehensive approach.

4. Debugging Assistance

We introduced a deliberately flawed code snippet and asked them to identify and fix the error.

Winner: Bard

Bard provided a more thorough explanation of the potential errors and how to fix them, along with clear usage instructions and expected output.

5. Third-party Plugins & UI Extensions

These extensions can enhance capabilities.

Winner: ChatGPT

ChatGPT offers a wider range of plugins and a mobile app, extending its functionality and usability. Bard currently lacks these features.

6. Ease of Use

Both offer user-friendly web interfaces. However, there are some key differences.

Winner: ChatGPT

ChatGPT provides easier conversation history management and doesn’t limit conversation length. Bard has a drafts feature, but overall, ChatGPT is more user-friendly.

7. Cost

Winner: Bard (for now)

ChatGPT offers a free tier with limitations and a paid tier with more features. Bard is currently free for everyone with a Google account. However, Bard’s future monetization plans are unclear.

Conclusion: ChatGPT Wins Narrowly, But Both Have Value

With a score of 4-3, It takes the lead. However, both tools have their strengths and weaknesses, making them valuable additions to a programmer’s arsenal. Here’s a quick summary:

  • ChatGPT: excels in code generation, problem explanation (with some reservations), and offers a wider range of plugins and a mobile app.
  • Bard: shines in code refactoring, debugging explanations, and is currently free to use.

Remember, these tools are not foolproof. The generated code might not always be accurate, so human oversight is crucial.


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