Codex CLI vs Gemini CLI vs Claude Code: Which is the Greatest?

In 2025, a number of AI coding assistants have been launched, which may be accessed instantly from the terminal. Codex CLI, Gemini CLI, and Claude Code are a number of the well-liked names that embed giant language fashions into command-line workflows. These programming instruments that may generate and repair code through pure language prompts are really unimaginable. We doc our analysis of all three of those throughout totally different duties to find out which is most helpful.

Every assistant relies on a complicated AI mannequin like o4-mini, Gemini 2.5 Professional, or Claude Sonnet 4 to boost productiveness. We place each in the identical setting and take a look at them with particular metrics on practical programming duties. Various from internet growth to information evaluation, by way of this, we intention to make the strengths of every agent clear!

Meet the Contenders: Codex CLI, Gemini CLI & Claude Code

The command line is shortly turning into a battleground for the subsequent era of AI coding assistants. Firms, together with OpenAI, Google, and Anthropic, have launched superior CLI-based AI coding assistants, every with very highly effective and spectacular capabilities instantly into the terminal. However what are the variations, and which is greatest to your workflow? Let’s go over the instruments. 

Codex CLI: OpenAI’s Code-Centric Terminal Agent

Codex CLI features like a wise terminal assistant for coding. It listens to what you say to it and creates code. Codex CLI has entry to your shell and file system. It may scaffold a challenge, write a operate, and repair a bug. Codex CLI is using OpenAI’s Codex fashions within the background. You utilize plain English to inform Codex CLI what code you prefer to for a process. Then the CLI suggests new code and recordsdata. Codex CLI helps a number of languages, together with Python, JavaScript, and Go.

Gemini CLI: Google’s Terminal Agent

Gemini CLI by Google brings collectively the strengths of the Gemini 2.5 Professional mannequin with entry to the terminal and filesystem with a purpose to create an uninterrupted coding and utility assistant for builders. It may be used for rather more than easy code era. Gemini CLI is adept at finishing duties in actual time, comparable to acquiring reside data or working shell instructions. Developed on the Google infrastructure and built-in with numerous instruments comparable to VS Code AI, Gemini CLI supplies utility throughout terminals and IDEs.

Claude Code: Anthropic’s CLI Assistant

Claude Code is a number one coding AI made for high-performance terminal workflows. It’s primarily based on Claude Sonnet 4 and might simply deal with end-to-end software program growth features. Comparable to writing new modules to working checks, to mechanically creating pull requests. Claude Code goals to supply depth, consistency, and certified codebase navigation. Whereas it’s skill-based and closed-sourced. So if you’re an expert software program developer on the lookout for AI that may perceive and evolve giant, complicated initiatives, Claude Code is for you.

Codex CLI vs Gemini CLI vs Claude Code: Abstract

How We Examined Them: Setup, Metrics & Duties

Testbed & Atmosphere: All of the CLI-based AI coding assistants have been examined utilizing a neighborhood workstation working Ubuntu 24.04. The brokers Codex CLI (primarily based on OpenAI’s o4-mini), Gemini CLI (Gemini 2.5 Professional), and Claude Code (Claude Sonnet 4) have been put in through npm or pip. Codex CLI and Claude required Node.js and legitimate API keys. Gemini CLI required a Google login for authentication.

Analysis Metrics That Matter: We evaluated every agent primarily based on 5 standards: 

• Code correctness
• Code era velocity
• Simplicity of prompts
• Output readability
• Dealing with of errors

These measures take a look at not simply efficiency, however how usable and dependable a developer can count on the brokers to be in an actual workflow.

Actual-World Duties Used within the Battle: Every agent was tasked with three duties to check versatility:

• Construct a recreation just like Tremendous Mario.
• Construct a Climate Clock that presents the time and the climate.
• Start exploratory information evaluation (EDA) in Python utilizing the Nike_Sales_Uncleaned.csv dataset.

Codex CLI vs Gemini CLI vs Claude Code: Activity-by-Activity Faceoff

Activity 1: Making a Tremendous Mario Recreation 

Aim: Construct a primary 2D Mario-style recreation

Immediate: “Create a primary 2D Tremendous Mario-style platformer recreation. The sport ought to function a easy tile-based structure with Mario standing on floor blocks, a background sky with clouds, a query mark block above him, and a inexperienced pipe close by. Embody primary mechanics like left/proper motion and leaping utilizing keyboard arrow keys. Simulate gravity and collision with platforms. Use pixel-art model graphics with embedded or referenced native belongings.”

Gemini CLI:

Codex CLI:

Claude Code:

CLI Comparability

• Claude Code: Greatest and most related of all three. It additionally makes use of the pixelated model, and the consumer has full management over Mario. It additionally exhibits the thriller packing containers for cash and power-ups, however nothing occurs when Mario hits them.
• Codex CLI: created an interface with a pixelated interface, however was not capable of play the sport as Mario is trapped contained in the inexperienced field.
• Gemini CLI: created an interface with a block format interface and capable of play the sport, however the factor is it doesn’t observe the unique guidelines, prefer it permits me to go by way of the objects and bounce mechanically when Mario reaches close to the sting with out urgent the bounce key.

Claude Code excels in recreation dealing with logic from each Codex and Gemini. It exhibits constant controls, gravity, and collision, and delivers probably the most immersive gameplay expertise.

Activity 2: Climate Clock App

Aim: Construct a clock UI with reside climate updates

Immediate: “Design and develop a visually wealthy weather-themed dynamic clock dashboard utilizing solely HTML, CSS, and JavaScript. The principle objective is to create a real-time clock interface that not solely shows the present time but in addition visually adapts to the time of day. Implement 4 animated background transitions representing dawn, midday, sundown, and night time, every with distinctive colours and animated components like transferring clouds, twinkling stars, or a rising/setting solar/moon, and supply a toggle between 12-hour and 24-hour time codecs. For an added layer of interactivity, embrace a piece that shows a rotating motivational or productiveness quote primarily based on the hour.”

Gemini CLI:

Codex CLI:

Claude Code:

CLI Comparability

• Claude Code: Claude Code offered probably the most visually profound and feature-complete end result. It carried out 4 animated themes with clean transitions and interactive components comparable to transferring clouds and celestial our bodies. Moreover, Claude Code got here with an auto-theme mode, shifting the backgrounds primarily based on system time. The 12/24-hour toggle and quote-randomization options have been seamlessly performed.

• Codex CLI: Codex CLI had carried out all the required features and execution, however lacked visible design and polish. The consumer expertise felt antiquated, with static styling and uninspired structure. Functionally, it was sound, however design execution was the weakest among the many three.

• Gemini CLI: Gemini CLI used a hard and fast background, i.e, no animation, which introduced down some visible richness. Nonetheless, Gemini was nonetheless a cleaner interface than Codex. Gemini made on a regular basis show and quote-randomization work appropriately, however lacked interactivity and dynamism within the general expertise.

To summarize, Claude Code was forward in UI logic and the general consumer expertise. It introduced collectively sound performance, partaking visible transitions, interactive components, and circulation within the consumer interface. Codex delivered on the essential practical necessities however lacked the UX, and Gemini had a average visible design however very low dynamism.

Activity 3: Performing EDA (Exploratory Knowledge Evaluation)

Aim: Clear, analyze, and visualize a dataset

Immediate: “Carry out Knowledge Evaluation and Exploratory Knowledge Evaluation (EDA) on the dataset offered in the identical listing. The whole evaluation needs to be carried out and saved in a Jupyter Pocket book file named eda.ipynb. Start by loading the dataset and inspecting its construction, together with column names, information varieties, and abstract statistics. Proceed to wash the info by dealing with lacking values, correcting information varieties if vital, and eradicating any duplicates. Conduct univariate evaluation to grasp particular person options, after which carry out bivariate and multivariate evaluation to uncover relationships between variables. Use clear and related visualizations to assist your insights. Manage the pocket book with correct Markdown headings and explanations for every step. Conclude with a minimum of three key observations or insights drawn from the info.”

Gemini CLI:

Codex CLI:

Claude Code:

CLI Comparability

• Claude Code: Claude Code produced an entire professional-grade EDA. It accomplished each piece of the instruction from the immediate, together with the output being organized into three folders:
  • A Plots folder containing all of the generated visualizations
  • A Code folder containing the clear, reproducible pocket book
  • The visuals have been applicable, and the insights have been reported clearly.
• Codex CLI: Codex CLI produced a usable however partial answer. It produced the required code and suitably adopted the EDA steps, however it didn’t produce any visualizations or present a abstract of essential insights. The pocket book didn’t have any ultimate analytical conclusions, nor markdown explanations to help in interpretation.
• Gemini CLI: Gemini CLI was unable to finish this process. It was unable to finish the EDA pipeline and finally produced an incoherent pocket book. There have been many cases of dataset loading failing, no visualizations, and lots of incomplete code blocks.

Claude Code is the one for EDA and information evaluation. It not solely completes the total analytical workflow but in addition organizes the outputs properly and delivers well-structured insights helpful for each single-user information work and team-based environments. Codex could possibly be a helpful backup; nonetheless, Gemini CLI shouldn’t be applicable for this.

Codex CLI vs Gemini CLI vs Claude Code: Total Evaluation

Claude Code offers a transparent construction and documentation, and is nice to execute. It dealt with the sport logic and error dealing with with out problem. Codex CLI was quick and versatile, however required some guide intervention. Gemini CLI gave a agency basis and appeared quick. Its polish and documentation have been missing; it suffered probably the most within the EDA task, lacking core outputs and structural completeness.

In velocity, Codex CLI was quickest, adopted by Gemini and Claude. Claude was the simplest for immediate engineering. Every CLI was suited nicely to particular workflows. Claude was sturdy on logic-heavy work, Codex could be greatest in speed-focused workflows, and Gemini was appropriate for primary structured implementations missing refinement.

Conclusion

Claude Code was one of the best throughout all duties, offering the very best quality code, consumer expertise, and full vary of options. Whereas it was not the quickest AI coding assistant, its completed merchandise have been polished, documented, organized, and preferrred for skilled workflows with a number of belief concerned. Codex CLI was the quickest, and an ideal alternative utilizing to creating fast prototypes or if there was a time constraint on the coding work. 

Gemini CLI was affordable for primary builds, however had points with not being quick, polished, or organized for a lot of varieties of labor. It had points with information evaluation duties that required organized or insightful content material. Total, all instruments have totally different matches, however Claude Code supplies probably the most constant depth with regards to being a command-line AI coding assistant.

Incessantly Requested Questions