Which is a Higher Coding Agent?

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

Builders can enhance code comprehension, pace 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 turn out to be much more thrilling with the launch of Gemini CLI, a light-weight, open-source substitute from Google that’s gaining reputation shortly.

Let’s now take a more in-depth take 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 in search of detailed walkthroughs, try our guides on every CLI instrument:

Set up

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

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. Verify Node.js model:

node --version

2. Guarantee it’s NodeJS model 22 or larger.
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 challenge listing’s .env file comprises the OPEN AI API Key, then we don’t want to do that job):

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. Verify Node.js model:

node --version

Guarantee it’s 18 or larger.

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

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 together 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 atmosphere utilizing the next entry:
         export GEMINI_API_KEY=”your-api-key”
5. Run Gemini CLI:

gemini

6. Or cross a immediate straight:

gemini "Hi there, 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 obtainable 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.
• Bear in mind, while you need to use your CLI for a sure challenge, ensure you have the present working listing set to the folder path the place your challenge exists. 

Operating our CLI Cases

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

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

Let’s first attempt it out with Codex CLI:

Codex CLI

If all the necessities have been glad, then we will begin with the exams.

Process 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 trustworthy, surprisingly good. Moreover, Codex CLI briefly asks us to grant entry to particular code segments, which we will grant or reject primarily based on our judgment. It supplies a decent report after taking an affordable period of time to mirror.

The report’s high-level goal, repository structure, key parts, front-end web sites, and property are all included, together with a abstract. Though I had given the primary recordsdata moderately ambiguous names, I used to be nonetheless shocked to search out that it might decode all the earlier iterations of the code recordsdata in chronological order.

Process 2 – Error Debugging

Since we enable the Codex CLI entry to our whole database, whether or not or not it’s non-public or protected, it is going to ask for our authorization earlier than studying any code snippets. If we allow it, it is going to entry our snippet appropriately. 

Total, it was in a position to recognise each minute mistake and infrequently provided fixes for some careless errors within the code, eradicating pointless parts that had an impression on a few of the latency barely.

Process 3 – Additions to Codebase

This concerned understanding how every module was outlined throughout varied directories and bridging the data 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 once we requested entry.

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

Gemini CLI

I preferred the Dracula theme.

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

Process 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 an alternative scans our whole database. However, in my expertise, it does provide a good overview, however it’s certainly not nearly as good as Codex by way of output.

Process 2 – Error Debugging

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

Process 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

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. Nevertheless, safety and privateness vulnerabilities should exist, so I might advise being cautious about what and the place in our codebase we grant these CLIs entry.  

Steadily Requested Questions

GenAI Intern @ Analytics Vidhya | Ultimate 12 months @ VIT Chennai
Enthusiastic about AI and machine studying, I am wanting to dive into roles as an AI/ML Engineer or Knowledge Scientist the place I could make an actual impression. With a knack for fast studying and a love for teamwork, I am excited to convey modern options and cutting-edge developments to the desk. My curiosity drives me to discover AI throughout varied fields and take the initiative to delve into knowledge engineering, guaranteeing I keep forward and ship impactful initiatives.