Which is a Higher Coding Agent?

Open-source CLI instruments have created a number of pleasure within the developer and AI communities. With the discharge of Claude’s Codex CLI, OpenAI’s Codex CLI, and, extra just lately, Google’s Gemini CLI, there’s a sudden improve in curiosity in CLIs typically. By incorporating AI assist into routine duties, these instruments are altering how builders use their terminals.

Builders can enhance code comprehension, velocity up debugging, and automate tough coding duties by utilising these CLIs. Instruments like Codex CLI assist customers write, analyse, and enhance code extra effectively by bringing sturdy AI-driven options like code era, refactoring, and inline documentation straight into the command line. The market has change into much more thrilling with the launch of Gemini CLI, a light-weight, open-source substitute from Google that’s gaining reputation rapidly.

Let’s now take a better have a look at how Gemini CLI and Codex CLI fare when put to the take a look at.

What are Gemini CLI and Codex CLI?

Gemini CLI: An open-source AI agent by Google that integrates Gemini fashions (like Gemini 2.5 Professional) into the terminal for builders.

Codex CLI: An open-source command-line instrument forked from OpenAI’s unique Codex CLI, now supporting a number of AI suppliers, together with Gemini 2.5 Professional. It permits builders to work together with massive language fashions within the terminal for duties like code era, refactoring, and script rationalization.

Should you’re on the lookout for detailed walkthroughs, take a look at our guides on every CLI instrument:

Set up

Earlier than continuing with the set up, be certain that the system necessities are happy.

System Necessities

NodeJS is a typical prerequisite for each the CLIs. You’ll be able to set up Node.js by following the directions on its official web page: https://nodejs.org/

Set up Steps for Codex CLI

1. Test Node.js model:

node --version

2. Guarantee it’s NodeJS model 22 or greater.
3. Set up Codex CLI globally:

npm set up -g @openai/codex

4. Or utilizing pnpm:

pnpm add -g @openai/codex

5. Set your OpenAI API key (if inside your mission listing’s .env file comprises the OPEN AI API Key, then we don’t want to do that process):

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

6. Add this line to your shell config file (e.g., ~/.bashrc, ~/.zshrc) for persistence.
7. Run Codex CLI:

codex

8. Or cross a immediate straight:

codex "clarify this codebase to me"

Set up Steps for Gemini CLI

1. Test Node.js model:

node --version

Guarantee it’s 18 or greater.

2. Set up Gemini CLI globally (really helpful):

npm set up -g @google/gemini-cli

3. Alternatively, run straight with out set up:

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

4. Authenticate:
   1. Default: Register along with your Google account when prompted (browser window will open).
   2. API Key (for superior use):
      1. Get your API key from Google AI Studio.
      2. Set it in your setting utilizing the next entry:
         export GEMINI_API_KEY=”your-api-key”
5. Run Gemini CLI:

gemini

6. Or cross a immediate straight:

gemini "Hey, are you able to assist me with coding?"

Issues to Preserve in Thoughts

• For each instruments, Node.js and npm (Node Package deal Supervisor) have to be put in and accessible in your system PATH.
• For Codex CLI, Node.js 22+ is required, whereas Gemini CLI works with Node.js 18+.
• Each require authentication through API keys or account login for full performance.
• On Home windows, Codex CLI is finest run through WSL2 for full compatibility.
• Keep in mind, whenever you wish to use your CLI for a sure mission, ensure you have the present working listing set to the folder path the place your mission exists. 

Working our CLI Cases

Let’s proceed to check the efficiency between the two fashions with 3 duties

• Constructing a working mannequin on a neighborhood host
• Studying a posh codebase and explaining the code
• Error debugging

Let’s first strive it out with Codex CLI:

Codex CLI

If all the necessities have been happy, then we are able to begin with the assessments.

Job 1 – Explaining our Codebase

We are able to see that Codex can present an in depth abstract of our code base, which was, to be sincere, surprisingly good. Moreover, Codex CLI briefly asks us to grant entry to particular code segments, which we are able to grant or reject primarily based on our judgment. It offers a decent report after taking an affordable period of time to mirror.

The report’s high-level objective, repository structure, key elements, front-end web sites, and property are all included, together with a abstract. Although I had given the principle recordsdata slightly ambiguous names, I used to be nonetheless shocked to seek out that it may decode all the earlier iterations of the code recordsdata in chronological order.

Job 2 – Error Debugging

Since we enable the Codex CLI entry to our total database, whether or not it’s personal or protected, it would ask for our authorization earlier than studying any code snippets. If we allow it, it would entry our snippet appropriately. 

General, it was capable of recognise each minute mistake and sometimes supplied fixes for some careless errors within the code, eradicating pointless parts that had an affect on among the latency barely.

Job 3 – Additions to Codebase

This concerned understanding how every module was outlined throughout numerous directories and bridging the information between every dependency to make sure that a brand new listing was created to construct the new.py recordsdata for the additions we had requested after we requested entry.

Let’s now try to look at how the Gemini CLI capabilities.

Gemini CLI

I preferred the Dracula theme.

Not like Codex CLI, the place we solely must export our OPENAI_API_KEY, we’ve got three other ways to log in right here: utilizing our Gmail account, copying the GEMINI_API_KEY from AIStudio, or utilizing Vertex AI credentials.

Job 1 – Clarify our Codebase

The principle distinction I noticed was that, in contrast to Codex CLI, which asks for entry to particular directories, Gemini skips this step and as a substitute scans our total database. However, in my expertise, it does supply a good overview, however it’s in no way nearly as good as Codex by way of output.

Job 2 – Error Debugging

In my view, Gemini’s response was considerably higher defined than Codex’s, because it was capable of determine the sorts of safety dangers, clarify them, and supply file names as references for additional investigation and steered adjustments. Moreover, providing an intensive technique to handle every of those errors would allow the code to be modified with out impairing its performance if the mandatory directions had been adopted.

Job 3 – Additions to Codebase

Gemini CLI wasn’t working for this workload, so no output was produced.

Gemini CLI vs Codex CLI: Ultimate Verdict

Additionally Learn: 10 Methods College students Can Use Cursor AI for Free

Conclusion

When evaluating the options of those two CLIs, I discovered that Codex affords extra performance than Gemini CLI. For the time being, each the CLIs are open-sourced and can finally have higher performance in future releases. 

Since a GPT mannequin analyses our code, Codex additionally affords better privateness by requesting entry to our codebases and modules in a manner that minimizes safety danger. Nonetheless, this doesn’t look like a case of the Gemini CLI requesting entry commonly; as a substitute, it asks when it needs to run the applying code. Moreover, we should always do not forget that the context on the appropriate facet of the terminal can be tracked by Gemini CLI. 

When mixed with extra clever vibe coding IDEs like Cursor, Windsurf, and others, such CLIs would undoubtedly open up new potentialities for vibe coding workflow and utility operation. Nonetheless, safety and privateness vulnerabilities should still exist, so I might advise being cautious about what and the place in our codebase we grant these CLIs entry.  

Steadily Requested Questions