You type a few lines of code into an AI tool, expecting instant results. But instead of running the code, it just gives you suggestions. Frustrating, right? It is because all the AI models do not work the same way; each has different strengths and weaknesses.
AI changed the way we learn programming, write code, and fix issues. But it has limits. Some AI tools can generate code, while others can execute it. That’s where the main difference between ChatGPT and DeepSeek comes in. ChatGPT can generate a code, but it doesn’t run it. On the other hand, DeepSeek can execute code in real time, making it more interactive for programmers. So, does ChatGPT run code? The short answer is no; it helps with coding but doesn’t execute it.
Can ChatGPT Run Code?
No, ChatGPT does not run code. While it doesn’t run the code, it can produce well-structured code in a number of programming languages. Instead, it works as a creative helper to help programmers in writing, understanding, and debugging code.
ChatGPT analyzes your request and offers a well-organized response when you ask it for code. Whether you need a PLC programming script, an HTML snippet, or a complex algorithm, it offers well-formatted code. However, you have to copy and run it in a proper coding environment.
ChatGPT is useful for solving coding problems. It suggests solutions, explains tricky concepts, and even helps with debugging. If you’re stuck, it can point out errors in your logic or suggest better approaches. Many developers use ChatGPT best practices to refine their coding and improve efficiency. It’s also a great tool to teach coding by breaking down concepts into simple explanations.
How DeepSeek is Different
Unlike ChatGPT, which only generates code, DeepSeek can run code in real-time. This means you can type a script, and it will execute it instantly, giving immediate results. This makes DeepSeek useful for testing, debugging, and learning by trial and error.
DeepSeek supports various programming languages, allowing users to execute Python scripts, test algorithms, and even run programming commands. It simplifies coding tasks by eliminating the need for an external environment to test the code.
The key difference between ChatGPT and DeepSeek is execution. ChatGPT helps by structuring and explaining code, while DeepSeek allows users to run and test it directly. This real-time execution is especially helpful for developers working on quick fixes or interactive coding projects.
DeepSeek was created by DeepSeek AI, a research-focused AI company pushing the limits of artificial intelligence. It uses the DeepSeek RI model, which enhances its ability to process and execute code efficiently. Developers can also use a DeepSeek AI prompt to generate and execute code in one step, making the workflow smoother.
When to Use ChatGPT and When to Use DeepSeek
Whether or not you should use DeepSeek or ChatGPT is based on what you are trying to do. ChatGPT would be the better option if you’re stuck on ideas or just beginning to learn to code. It’s great for brainstorming ideas, describing complex ideas, and giving easy code examples. For example, if you’re learning about sorting data or require a quick rundown of object-oriented programming, ChatGPT can break down the basics and provide effective examples.
DeepSeek, on the other hand, is best for testing and running code in real-time. If you’re coding on a project that has constant changes and quick feedback required, DeepSeek is a great choice. For example, if you’ve written a function and want to test it out, you can just run it in DeepSeek to get the output in real-time. This can be quicker compared to switching back and forth between your code editor and testing environment.
Overall, use ChatGPT to learn and come up with ideas, and use DeepSeek when you want to run and test your code in real-time.
Limitations of ChatGPT in Code Execution
ChatGPT can generate code, but like every other AI, it has some limitations. ChatGPT might not be the best choice when it comes to actually running a code.
No Real-Time Execution
Code cannot be run or tested in real time via ChatGPT. This means that although it can give you parts of code in Python, HTML, or JavaScript, it doesn’t actually run them. Users cannot see results or troubleshoot errors through ChatGPT directly. This limits its practical application for testing and debugging.
No Access to Development Environments
ChatGPT doesn’t have the capability to interact with coding environments, databases, or external APIs. For example, it is unable to access servers for testing, run a script that works with web pages, or search a database. To run the code, users must copy and paste it into their own Integrated Development Environment (IDE).
Lack of Contextual Understanding in Execution
While ChatGPT can generate a wide range of code structures, it lacks the deeper understanding of runtime environments. This makes it challenging for it to predict how a particular code will behave when executed.
How to Work Around These Limitations
While ChatGPT performs well in providing structured code and offering insights, real-time execution requires an external environment. Here are some ways to work around this limitation:
Test on External Platforms
To bypass this limitation, developers can test the code produced by ChatGPT using coding platforms such as Replit, Jupyter Notebooks, or integrated development environments such as Visual Studio Code. After generating the code, paste it into the platform, execute it, and verify the output for bugs or unusual behavior.
Debugging with ChatGPT’s Assistance
Users can apply ChatGPT’s ability to explain errors and suggest fixes. After running the code on a local environment or online platform, any errors can be shared with ChatGPT to get debugging suggestions.
Leverage Pre-Built Libraries and Tools
ChatGPT can help developers by suggesting libraries, frameworks, or tools for testing and running code. By using external tools and integrating them with the generated code, users can get more functionality.
While ChatGPT is powerful in generating code, users will need to rely on external platforms for testing and execution, as ChatGPT does not run code directly.
Final Thoughts
When it comes to coding, ChatGPT and DeepSeek AI have different uses. ChatGPT is great for creating structured code, debugging, and for explanations. But if you want to test code in real time, DeepSeek is a much better option.
When selecting an AI, consider what you require. If you want AI to generate code with specific instructions, you should choose ChatGPT. But if you want to test and run your code immediately, you should choose DeepSeek AI.
So, the answer to “Does ChatGPT run code? Is no. However, you may close the gap and improve your coding skills with the correct tools.
