Gemini Cli vs Codex Cli: Which is a better coding agent?

Open-Source CLO Tools created a great excitement of the development and communication of AI. With Claude’s Codex Cli, OpenI’s Codex Cli and recently, Google Gemini Cli, there is a sudden increase in interest in cli in general. By incorporating AI support into routine tasks, these tools change as developers use their terminals.

Developers can improve code understanding, speed up tuning and automatic difficult to coded tasks using these Clis. Tools like Codex CLI help users to write, analyze and more efficiently improve the code by bringing strong controlled and, such as code generation, refactoring and inline documentation directly to the command line. The market has become even more exciting to start Gemini CLI, lightweight substitutes with Google’s open source, which quickly gains popularity.

Let’s take a closer look at how Geni Cli and Codex Cli get to the test.

What are the Gemini Cli and Codex Cli?

Gemini CLI: Open-Source AI Agent from Google, which integrates Gemini (like Gemini 2.5 Pro) into a developer terminal.

CODEX CLI: Command line tool with an open source code expanding the original Codi Cli Openi, now supporting multiple AI providers, including Gemini 2.5 Pro. It has developers to develop developers to interact with large language models in the terminal for tasks such as code generation, refractoring and the script explanation.

If you are looking for detailed passages, check out the guide to each clies:

Device

Before controlling the installation, ensure that the system requirements are met.

System requirements

Nodejs is a common prerequisite for both Clis. Node.js can be installed according to the instructions on her officials page: https://nodejs.org/

Installing steps for CODEX air conditioning

1. Check the Node.js version:

node --version

2. Enture it is nodejs version 22 or high.
3. Install CODEX CLI worldwide:

npm install -g @openai/codex

4. Gold with PNPM:

pnpm add -g @openai/codex

5. Set the OPENAI API (if the Open AI API key contains within the project directory file, we do not need to perform this task):

export OPENAI_API_KEY="your-openai-api-key"

6. Add this line to the Shell configuration file (eg ~/.bashrc, ~/.zShrc) for persistence.
7. Run Codex CLI:

codex

8. Or directly to pass on the challenge:

codex "explain this codebase to me"

Steps to air conditioning Gemini

1. Check the Node.js version:

node --version

It is 18 or higher.

2. Install Gemini CLI Globally (Recommended):

npm install -g @google/gemini-cli

3. Alternatively run directly without installation:

npx https://github.com/google-gemini/gemini-cli

4. Authenticate:
   1. Default: Login to your Google Account when the prompt (window opens the browser).
   2. API key (for advanced use):
      1. Get the API key from Google AI.
      2. Set it in your environment using the following item:
         Export Gemini_api_Key = “Your-Dep-Cooy”
5. Start Gemini Cli:

gemini

6. Or directly to pass on the challenge:

gemini "Hello, can you help me with coding?"

Things that need to be kept in mind

• For both tools, they must be installed and available on the Node.js and NPM system routes (node manager).
• Node.js 22+ is required for Codex CLI, while Gemini Cli works with Node.js 18+.
• Both require authentication using API keys or login to full functionality.
• On Windows, Codex Cli is best launched via WSL2 for full compatibility.
• Keep in mind that if you want to use a CLI for a particular project, make sure you have a current workmark set to the folder path where your project exists.

Run for Instance Air

Let’s proceed to compare the performance between the two models with 3 tasks

• Building a working model on a local host
• Reading a complex base base and explanation of code
• Tuning

Try it first with CODEX CLI:

CODEX CLA

If all the requirements have been met, we can start tests.

Task 1 – Explanation of our code base

We see that Codex can provide a detailed summary of our code base, which was to be honest, surprisingly good. In addition, Codex CLI temporarily asks us to give access to specific code segments that we can grant or reject on the basis of the judgment. It provides respectable postponement after arresting adequate love of time to reflect.

Included are high-level purposes, Restilian layout, key components, front-end websites and assets, together with summary. Although I gave the main files somewhat ambiguous names, I was still shocked when I found it could be all the previous iterations of the code file in the chronological order.

Task 2 – Tuning of Errors

Because we enable Codex CLI access to our entire database where it is private or protected, it will ask for our permission before reading any code excerpts. If we allow it, it will approach our snippet.

Overall, he was able to recognize an error every minute and occasionally offered repairs for some careless code errors and remove unnecessary portions that had a slightly impact on part of the latency.

Task 3 – Entry to code base

This included an understanding of how each module was defined in different addresses and bridge knowledge between each addiction to ensure that a new directory was created to create a new .py File files we requested when we asked for access.

Let’s wait for the Gemini Cli to work.

CRICA Gemini

I liked the topic of Dracula.

Unlike CODEX CLI, where we only need to export our OpenI_API_Key, we have three different ways to log in: using our Gmail account, copy gemini_api_key from Aistudio or using Vertex AI login data.

Task 1 – Explain our code base

The main difference I observed was that, unlike the Codex CLI, which asks for access to specific directories, Gemini skips this step and instead scans our entire database. In my experience, however, it offers a decent overview, but by no means is it as good as Codex in terms of output.

Task 2 – Tuning of Errors

In my opinion, Gemini’s answer was significantly better explained than Codex because she was able to identify the types of security risks, explain them and provide file names as references to further investigation and proposed changes. In addition, the offer of a thorough strategy to add up to each of these incorrect bars would allow you to modify the code without deteriorating its functionality if the necessary instructions were observed.

Task 3 – Entry to code base

Gemini CLI did not work for this workload, so no output was created.

Gemini Cli vs Codex Cli: Final verdict

Also read: 10 ways that students can use free AI cursor

Conclusion

When comparing the functions of these two CLIS, I found that the CODEX menu: at the moment both CLIS are open and eventually have better functionality in future editions.

Sale GPT analysis Our code, CODEX also offers more privacy by requiring access to our code and modules in a way that minimizes security risk. However, it is not a case of CLI Gemini, which requires access regularly; Instead, he asks when he wants to run the application code. In addition, we should remember that the context on the right side of the terminal is also monitored by Gemini Cli.

Combined with more intelligent Vibrations of IDE coding, such as cursor, Windsurf and more, such a CLIS would undoubtedly open up a new option for the workflow and operation of vibration applications. However, the vulnerability of the security and protection of personal data can still exist, so I would recommend being careful about what and where in our code base we provide these Clis access.

Frequently asked questions