AI-Coding Showdown: Spheron GPT vs. GitHub Copilot - The Future of Code Generation

AI-Coding Showdown: Spheron GPT vs. GitHub Copilot - The Future of Code Generation

The Two AI Code Generators That Are Changing the Way We Code

In this blog, we present an in-depth comparison between two powerful AI-driven coding tools: Spheron GPT and GitHub Copilot.

Spheron GPT is a CLI tool that utilizes the ChatGPT 3.5 turbo model from OpenAI to generate code files, While GitHub Copilot serves as a code assistant, offering context-aware code suggestions. Spheron GPT generates complete files, offers customization options, and works in any text editor. In contrast, GitHub Copilot suggests code within supported IDEs like Visual Studio Code. Spheron GPT proves faster in code generation, supports file generation based on other files, and provides code transpilation, which GitHub Copilot lacks. This analysis will help you determine which one best suits your coding needs.

Product Overview

Spheron GPT: Enhancing Code Generation with Turbocharged AI

Spheron GPT is a command-line interface (CLI) tool specifically designed to enhance code generation capabilities using the advanced ChatGPT 3.5 turbo model developed by OpenAI. It streamlines the process of creating code files by allowing users to generate single or multiple files directly from the outputs produced by ChatGPT.

Key Features of Spheron GPT :

  1. File Generation: SpheronGPT allows users to generate code files directly from the outputs produced by ChatGPT. By running the tool within the desired directory, developers can effortlessly create single or multiple files, depending on their requirements. This feature eliminates the need for manual code writing and accelerates the initial stages of software development.

  2. Code Customization: SpheronGPT empowers developers to leverage the generated code as a starting point and customize it further to suit specific needs. By providing a solid foundation, the tool enables developers to focus on higher-level problem-solving and implementation details rather than spending time on routine code composition.

  3. Integration with Existing Projects: With SpheronGPT, incorporating complex code snippets into existing projects becomes seamless. Developers can generate intricate pieces of code that align with the structure and requirements of their ongoing projects. This capability saves time and ensures consistency in coding style and adherence to project standards.

Github Copilot

Github Copilot is a cloud-based artificial intelligence tool developed by GitHub and OpenAI to assist users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments by autocompleting code.

Key Features of Github Copilot:

  1. AI-based suggestions: Copilot provides context-aware tips based on coding style conventions and project context, enabling personalized recommendations.

  2. Problem-solving focus: GitHub Copilot helps developers reduce time spent on repetitive code patterns and boilerplate code by suggesting code solutions.

Feature Comparison Chart


Spheron GPT

GitHub Copilot

Code generation approach

Generates entire files at once

Provides context-aware suggestions and code completion

Time to generate code



Generate files based on other files



Code Transpilation



Code Quality

Code written by Spheron GPT is likely to compile and run properly 

Need more human intervention and need an understanding of the language 

Code debugging and fixes







More versatile

Less versatile

Open source




Free for now

Paid subscription only

Feature comparison in Detail

Code Generation Approach

GitHub Copilot functions primarily as a code assistant, offering context-aware suggestions and code completion to support developers during their coding process. It assists by providing suggestions for individual lines of code or entire functions based on the context and existing code patterns. This interactive approach empowers developers to leverage AI-generated code snippets to expedite their coding tasks and boost productivity.

In contrast, Spheron GPT is purposefully designed as a code generator. Leveraging the powerful ChatGPT 3.5 turbo model, it can seamlessly generate entire code files by using the AI model's outputs. This unique capability streamlines the code creation process, minimizing the need for extensive manual intervention. Spheron GPT's code generation prowess is particularly useful for automating repetitive tasks and swiftly building complete code structures in a single step.

Time Comparison

Spheron GPT demonstrates superior speed in code generation compared to GitHub Copilot. The utilization of the ChatGPT 3.5 turbo model in Spheron GPT enables swift and efficient code generation, making it an ideal choice for developers who prioritize quick and precise code solutions. On the contrary, while GitHub Copilot offers context-aware suggestions, it may take a little longer to provide code completion due to its interactive nature.

Generate Files Based on Other Files

Spheron GPT stands out by offering the capability to generate entire files based on the outputs generated by ChatGPT. This feature streamlines the coding process, enabling developers to create complete code files in one go.

In contrast, GitHub Copilot does not support the direct generation of files based on other files. Instead, it focuses on providing suggestions for code completion within an existing file.

Code Transpilation and Debugging & Fixes

Spheron GPT offers a significant advantage over GitHub Copilot with its diverse functionality. It supports code transpilation, translating code between programming languages, and goes beyond by providing code debugging and fixes, simplifying the development process.

Developers can seamlessly integrate code across environments using Spheron GPT. At the same time, GitHub Copilot lacks these specific functionalities, making Spheron GPT a comprehensive and powerful tool for a wide range of coding tasks.

GitHub Copilot in IDE vs. Spheron GPT in Terminal

GitHub Copilot relies on integrated development environments (IDEs) for its functionality. Users have to work within supported IDEs like Visual Studio Code, Visual Studio, Neovim, or JetBrains to access GitHub Copilot's code completion and suggestion features. This IDE-centric approach may limit its usage for developers who prefer different coding environments or specific text editors not supported by Copilot.

On the other hand, Spheron GPT operates as a command-line interface (CLI) tool, making it independent of any particular IDE. It gives developers the freedom to use their preferred tools.


In conclusion, both Spheron GPT and GitHub Copilot offer valuable AI assistance, but they cater to different coding needs. Spheron GPT excels in rapid code generation, customization, and seamless integration into various text editors, while GitHub Copilot serves as an effective code assistant for context-aware suggestions and faster code completion within supported IDEs. The choice between these tools depends on individual preferences and project requirements, and both tools contribute to elevating the coding experience through AI assistance and the productivity of developers in their unique ways.

If you are interested in accessing Spheron GPT, please join the Discord Community and inquire about the process to get whitelisted.


Spheron GPT Tutorial: Link
GitHub Copilot Integration Guide: Link
ChatGPT 3.5 Turbo Model Overview: Link