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Coding with Google Bard vs ChatGPT: Which Is Better?

November 27, 2023

Programmers can profit directly from generative AI. It facilitates the authoring and debugging of code, which lightens the load on our already hectic lives. However, rival programs like Google Bard and ChatGPT have emerged, raising the question of which is best for me to utilize.

We pit these tools against each other in the final competition to see which programming tool now has the most features.

ChatGPT and Google Bard: What’s the difference?

ChatGPT and Google Bard

The Large Language Models (LLMs) that underpin ChatGPT and Bard represent the primary distinction between the two. Bard employs the Language Model for Dialogue Applications (LaMBDA), whereas ChatGPT uses the Generative Pre-trained Transformer 4 (GPT-4). Moreover, OpenAI produced ChatGPT, whereas Google developed Bard.

Both are capable of doing fairly comparable tasks. ChatGPT can be used by programmers for:

  • Suggestions: For functions and other code constructions, both models are capable of recommending the appropriate syntax and arguments.
  • Code that you have begun writing can be finished by it.
  • Debugging: It can assist you in locating mistakes and issues in your code.
  • Explanation: It can provide an explanation for the code you enter or that it creates.

A sizable dataset, comprising Common Crawl, Wikipedia, books, articles, documents, and information retrieved from the internet, was used to train both models. Bard, on the other hand, differs slightly from ChatGPT in that it was trained mostly on generic information that had been scraped, whereas Bard was trained on online discussions and dialogues.

Bard is still under development slightly more than ChatGPT, but both products are. Here’s how they perform in comparison to one another, though, to fully demonstrate how these distinctions matter in real life.

Testing ChatGPT and Bard against each other

ChatGPT and Bard

Based on our assessment of which aspects were most pertinent, we selected seven to compare the chatbots against each other: code generation, problem-solving, refactoring code, debugging support, third-party plugins/UI extensions, cost, and simplicity of use. Let us state up front that this is based on a few experiments along with our practical experience thus far, not a rigorous scientific comparison.

1. Code generation

The main purpose for why we desire it, isn’t that right? The following instruction was entered into the system: “Write a function in Python that returns a list of 100 prime numbers.” 

Bard’s attempt at coding

It looks good, but is it functional? According to our experience, chatbots occasionally write code that malfunctions or even invents new functionality! For this reason, it would be extremely detrimental to have AI-generated code in production without human inspection. Let’s give it a try and see.

ChatGPT’s coding attempt

This code provides a function generate_primes(n) that accepts an integer n as input and produces a list of all prime numbers up to n when we run the same prompt through ChatGPT. The primes are produced via the Sieve of Eratosthenes method.

Each of these yielded a useful outcome. This is where ChatGPT’s example shines because it’s much clearer and has a lot less code. It also accurately understood our ambiguous prompt. This is only one use scenario, though, since chatbot responses are known to differ greatly according to the language they are employing (less widely used or documented languages tend to have more faults) and the intricacy of the inquiry. Now let’s see how various use situations are handled by Bard and ChatGPT.

2. Problem Solving

Let’s examine these LLMs’ responses to an issue. Instead of just asking them to create a generic function, let’s provide them with the following Leetcode programming problem:

Create JavaScript code that makes all arrays more functional and allows you to call the array. Any array may be used with the last() function to get the final entry. It should return -1 if the array has no elements.

ChatGPT’s problem-solving

ChatGPT not only resolves the issue but also clarifies it. Very cool! But first, let’s examine if the code truly passes the tests using leetcode.

It appears like ChatGPT was able to resolve the issue right away! It’s Bard’s turn to take the lead now.

Bard’s problem solving

Alright, so Bard’s description of how the code functions wasn’t as detailed as it might have been. That being said, if you compare what ChatGPT and Bard generated, they are almost exactly the same. Were they examining one another’s assignments?

Since we can’t just rely on Bard’s word for it, we perform the test using Leetcode, and…

Yes, it does! This makes sense considering that the response was almost exactly the same as ChatGPT’s.

In terms of problem-solving, choosing between the two is difficult. Even though the outcomes are about the same, ChatGPT explains the code much better, which is helpful if you want to learn how to fish rather than relying on ChatGPT to do it all for you. Our overall experience with ChatGPT has been as follows: in addition to providing a potential solution for your issue, ChatGPT also provides further guidance.

3. Refactoring Code

Assume for a moment that you wish to discover a method that is more efficient. Obtaining an alternative perspective on your code is really beneficial, and in contrast to your coworkers (should you have any), these resources are constantly available and cost-free to review your work. So let’s watch how it performs! This is the example that we gave you.

ChatGPT’s refactoring attempt

Thus, ChatGPT’s answer has been somewhat ambiguous. It offers a short explanation of the code and recommends using a ternary operator, both of which are worthwhile. It seems like it could have done a little bit more, though. Watch how Bard responds to the same task.

Bard’s refactoring attempt

Whoa! Like chalk and cheese, ChatGPT and Bard are not the same; Bard has unquestionably gone above and beyond. In addition to providing optimized code, it also displays benchmark results and benchmark creation code.

In general, Bard does slightly better when it comes to refactoring. This is probably partly because ChatGPT is only an LLM at the moment, whereas Bard is a Large Language Model (LLM) that also utilizes information from search engines. It should be noted, nevertheless, that ChatGPT is already beta testing a “Search with Bing” tool and making it available to free users. As a result, ChatGPT could soon improve significantly in terms of code restructuring. But for the time being, we must concede Bard’s victory.

4. Debugging assistance

There are bugs in life. Let’s test how well each tool handles a clearly broken piece of code by throwing it at them. Try to identify it before Bard and ChatGPT do! This is the exercise we performed: The following code contains an error; debug it. Provide code that uses it to correct any potential mistakes.

ChatGPT’s debugging attempt

Okay, ChatGPT responded to us and said that in order to avoid a {ZeroDivision} mistake, we must add some logic. It describes the issue and provides a way to accomplish so. It’s Bard’s time now.

Bard’s debugging attempt

Bard discovered a similar issue with ChatGPT’s function. However, Bard has provided an even more thorough explanation. It describes potential problems, how to resolve them, how to utilize the function, and what the result would be. Oh my!

In general, we’ve seen that Bard provides considerably more detailed responses and explanations when it comes to troubleshooting. While there have been instances where ChatGPT has identified issues more effectively, Bard generally gives the user more understandable examples.

We’re deadlocked 2-2 after Bard wins this one. Can any of them end the impasse?

5. Third-party plugins & UI extensions

An LLM’s functionality may be greatly expanded by adding a third-party plugin to it. For example, we can enable code execution in chat conversations or allow integration with Zapier. 

Currently available as a beta feature, ChatGPT provides over 80 plugins to its premium members. Check out our post “The best ChatGPT plugins for developers” to learn more about a few of these. Here’s an illustration of ChatGPT’s current plugin store:

I’m afraid there’s nothing to show you because it doesn’t exist! There is currently no timeline, however, it is reported to be on the plan.

For those who prefer an API over the web interface, ChatGPT and Bard both have one. We were unable to test Bard’s API, though, as it is still only accessible via invitation. Nonetheless, ChatGPT’s API is quite comprehensive and full. Additionally, ChatGPT has an official mobile app that is incredibly helpful for ideation and surprisingly easy to use.

We have to award ChatGPT the point for this one because Bard either doesn’t have the features yet or hides them behind an invite list.

6. Ease of Use

Alright, to start, using Bard and ChatGPT are both rather simple. Both of them feature an online interface where you can enter a question and receive an answer. Quite simple, huh? They are both able to keep context during their “conversations” as well. There are some distinctions between the two, though.

The way ChatGPT records your discussions is one significant distinction. They are constantly available, kept on the left side of the screen, and have no length restrictions. They are also removable at any time.

By contrast, Bard does not let you save or retrieve previous chats. While you can see what you’ve looked for and view your history, you are unable to click to resume a discussion like you do with ChatGPT. Only the text you entered for a prompt is visible. Furthermore, Bard sets a time limit on the chat, so if it drags on too long, you have to restart.

The “drafts” feature is one that Bard has over ChatGPT. It’s useful that Bard gives you access to a set of drafts so you may go over various answers to your prompt. Nevertheless, we discovered ChatGPT to be more robust and user-friendly despite this.

7. Cost

Cost information should be included with every tool, isn’t that right? There are two versions of ChatGPT: ChatGPT Plus, which costs $20 a month and is available for free. Priority access to new features, faster response times, improved results from the GPT-4 model, real-time internet searching features, plugins, and access during peak hours are all available to premium users.

Bard, on the other hand, is available to everybody with access. Obtaining this access necessitates either a Google Workspace account for which your admin has granted access to Bard (which might be a little frustrating if they haven’t) or a personal Google Account that you control independently. 

Though Bard presently wins by default since it’s free vs. freemium, it’s likely to be monetized at some time.


ChatGPT and Bard are two AI tools that offer similar capabilities for programming. ChatGPT uses the Generative Pre-trained Transformer 4 (GPT-4), while Bard uses the Language Model for Dialogue Applications (LaMBDA). Both models were developed by OpenAI, while Bard was built by Google. Both tools can suggest correct syntax and parameters for functions and code constructs, complete code, identify errors, and explain code. Both models were trained on a massive dataset, but Bard was trained on web conversations and dialogues. Both products are still under development, with Bard being more advanced than ChatGPT.

Tests were conducted on code generation, problem-solving, refactoring code, debugging assistance, third-party plugins/UI extension, ease of use, and cost. ChatGPT’s code generation was found to be cleaner and more accurate, while Bard’s response was more complex and error-prone. In conclusion, ChatGPT is the more feature-rich tool for programming purposes.

ChatGPT and Bard are two Large Language Models (LLMs) that offer various features and capabilities. ChatGPT is known for its problem-solving capabilities, providing a detailed explanation of the code, while Bard offers a more comprehensive approach. Both tools produce nearly identical results, but ChatGPT provides a more detailed explanation, making it easier for users to learn and apply the knowledge.

Both tools offer refactoring assistance, providing a different perspective on code and offering optimized solutions. However, Bard surpasses ChatGPT in refactoring, offering optimized code, benchmark results, and benchmark results. This is likely due to the use of search engine information in both tools.

Both tools also provide debugging assistance, allowing users to identify and fix potential errors in their code. ChatGPT provides a response to add logic to prevent a `ZeroDivision` error, while Bard provides a more detailed explanation, highlighting possible errors, guiding usage, and providing output. Overall, ChatGPT and Bard offer valuable tools for problem-solving, refactoring, and debugging, respectively.


Is Bard AI good for coding?

Although Bard can complete some of our coding activities, it really failed every one of them.

What is better than ChatGPT for coding?

GitHub- One of the greatest websites with multi-language coding capabilities is Copilot, similar to ChatGPT. compatible with well-known coding programs such as JetBrains, Neovim, and VS Code.

Is Google Bard more accurate than ChatGPT?

Text request generation and summarization are effectively handled by ChatGPT. Bard responds to queries more effectively and with more pertinent details.