codex vs gemini-cli

The two are close in size: 121.6k stars for codex, 106.8k for gemini-cli. Over the days we have tracked them codex moved +23.1% and gemini-cli +0.7%, so codex is growing faster right now.

gemini-cli leads on context depth and noise control and customization and model freedom. codex does not take any axis by a clear margin.

Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.

Where they stand today

A lightweight, local-first terminal coding agent that you can install and run with one command while signing in to ChatGPT or using your OpenAI API key.

Stars
121.6k
Tracked growth
+23.1%
Maturity
Last commit
5h ago
Language
Rust
License
Apache-2.0
Cost to run
Sign in with a ChatGPT plan or use your OpenAI API key

Terminal-first access to Gemini 3 with multimodal models, a 1M-token context window, built-in Google Search grounding, and MCP extensibility.

Stars
106.8k
Tracked growth
+0.7%
Maturity
Last commit
9h ago
Language
TypeScript
License
Apache-2.0
Cost to run
Free tier (60 req/min, 1,000 req/day); usage-based billing with API key
0%+23%52 tracked days
openai/codexgoogle-gemini/gemini-cli

Six axes, head to head

Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.

Axiscodexgemini-cli
Context depth
How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository.
Diff/file only
Whole-repo analysis
Noise control
How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only.
None mentioned
Config & trusted folders
Customization
How far it bends to your team: custom rules, prompts, style guides, per-path config.
No customization
Extensible configs & extensions
Privacy
Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only.
Cloud (ChatGPT/API)
Cloud API (your key)
Model freedom
Whether you can point it at any provider, or it is wired to one.
OpenAI only
Gemini + Vertex
Setup ease
What it takes to get a first useful run out of it.
One-command install
One-command run

Which one to pick

Pick codex if…

Easy setup — one-command install to run a local CLI coding agent that integrates with your ChatGPT plan or OpenAI API key.

Runs in cli, ide. Works with openai.

Pick gemini-cli if…

Easy setup — run instantly with npx to get Gemini 3 access in your terminal for large-context code understanding, GitHub PR review, and extensible tools.

  • Context depth: Whole-repo analysis (5/5 against 1/5)
  • Noise control: Config & trusted folders (3/5 against 1/5)
  • Customization: Extensible configs & extensions (5/5 against 1/5)
  • Model freedom: Gemini + Vertex (3/5 against 1/5)
Runs in cli, github-action, ci, pr-bot, ide. Works with gemini, other-fixed.

What people want from each one

Questions people ask

Is codex better than gemini-cli?

gemini-cli leads on context depth and noise control and customization and model freedom. codex does not take any axis by a clear margin. codex is worth picking when easy setup — one-command install to run a local CLI coding agent that integrates with your ChatGPT plan or OpenAI API key.

Which of codex and gemini-cli keeps my code private?

codex: Cloud (ChatGPT/API) (3/5). gemini-cli: Cloud API (your key) (3/5).

What does each one cost to run?

codex: Sign in with a ChatGPT plan or use your OpenAI API key. gemini-cli: Free tier (60 req/min, 1,000 req/day); usage-based billing with API key.

Full profiles: openai/codex and google-gemini/gemini-cli. Everything else in CLI coding agents.