codex vs pi

The two are close in size: 121.6k stars for codex, 102.0k for pi. Over the days we have tracked them codex moved +23.1% and pi +42%, so pi is growing faster right now.

They split the axes: codex leads on setup ease, pi on context depth and customization and model freedom.

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

An open-source, self-extensible coding agent harness that bundles a unified multi-provider LLM API, agent runtime, CLI and terminal UI in one project.

Stars
102.0k
Tracked growth
+42%
Maturity
Last commit
24m ago
Language
TypeScript
License
MIT
Cost to run
Your API key for cloud models
0%+42%52 tracked days
openai/codexearendil-works/pi

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.

Axiscodexpi
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
Diff + related files
Noise control
How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only.
None mentioned
None mentioned
Customization
How far it bends to your team: custom rules, prompts, style guides, per-path config.
No customization
Config & extensions
Privacy
Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only.
Cloud (ChatGPT/API)
Self-hostable
Model freedom
Whether you can point it at any provider, or it is wired to one.
OpenAI only
Multiple providers
Setup ease
What it takes to get a first useful run out of it.
One-command install
Config + API key

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.

  • Setup ease: One-command install (5/5 against 3/5)
Runs in cli, ide. Works with openai.

Pick pi if…

Privacy-friendly — can run locally or in a container while supporting multiple LLM providers via a unified API.

  • Context depth: Diff + related files (3/5 against 1/5)
  • Customization: Config & extensions (3/5 against 1/5)
  • Model freedom: Multiple providers (3/5 against 1/5)
Runs in cli. Works with openai, anthropic, gemini, byok.

What people want from each one

Questions people ask

Is codex better than pi?

They split the axes: codex leads on setup ease, pi on context depth and customization and model freedom. 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 pi keeps my code private?

codex: Cloud (ChatGPT/API) (3/5). pi: Self-hostable (4/5).

What does each one cost to run?

codex: Sign in with a ChatGPT plan or use your OpenAI API key. pi: Your API key for cloud models.

Full profiles: openai/codex and earendil-works/pi. Everything else in CLI coding agents.