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## Why `rust-ci-full` was paying the full Cargo nextest build-and-run cost once per platform, with Windows ARM64 as the long pole. This change moves the heavy work into one reusable per-platform flow: build a nextest archive once, then replay it across four shards so the platform lane spends less time running tests serially. For Windows ARM64, the archive is cross-compiled on Windows x64 and replayed on native Windows ARM64 shards so the slow ARM64 machine is used for execution rather than compilation. ## What changed - split the `rust-ci-full` nextest matrix into five explicit per-platform reusable-workflow calls - add `.github/workflows/rust-ci-full-nextest-platform.yml` to build one archive, upload timings/helpers, replay four nextest shards, upload per-shard JUnit, and roll the shard status back up per platform - add Windows CI helpers for Dev Drive setup and MSVC ARM64 linker environment export so the Windows ARM64 archive can be produced on Windows x64 - keep the existing Cargo git CLI fetch hardening inside the reusable workflow, since caller workflow-level `env` does not flow through `workflow_call` - document the archive-backed shard shape in `.github/workflows/README.md` - raise the default nextest slow timeout to 30s so the sharded full-CI path does not treat every >15s test as stuck ## Verification - validated the archive/shard flow with live GitHub Actions runs on this PR branch - Windows ARM64 cross-compile latency on completed runs: - https://github.com/openai/codex/actions/runs/26118759651: `34m30s` lane e2e, `17m16s` archive build, `9m55s` shard phase - https://github.com/openai/codex/actions/runs/26120777976: `30m36s` lane e2e, `17m21s` archive build, `6m50s` shard phase - comparable pre-cross-compile sharded Windows ARM64 runs were `55m01s`, `50m21s`, and `46m42s`, so the completed cross-compile runs improved the lane by roughly `12m` to `24m` versus the prior range - latest corrected cross-compile run: https://github.com/openai/codex/actions/runs/26120777976 - Windows ARM64 archive built successfully on Windows x64 - native Windows ARM64 shards started immediately after the archive upload - 3/4 Windows ARM64 shards passed; the failing shard hit the same existing `code_mode` test failure seen outside this lane - downloaded failed-shard JUnit XML from the validation runs and confirmed the remaining red is from known test failures, not archive/shard wiring - no local Codex tests run per repo guidance ## Notes - this PR does not change developers.openai.com documentation
npm i -g @openai/codex
or brew install --cask codex
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.
If you want the desktop app experience, run
codex app or visit the Codex App page.
If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.
Quickstart
Installing and running Codex CLI
Install globally with your preferred package manager:
# Install using npm
npm install -g @openai/codex
# Install using Homebrew
brew install --cask codex
Then simply run codex to get started.
You can also go to the latest GitHub Release and download the appropriate binary for your platform.
Each GitHub Release contains many executables, but in practice, you likely want one of these:
- macOS
- Apple Silicon/arm64:
codex-aarch64-apple-darwin.tar.gz - x86_64 (older Mac hardware):
codex-x86_64-apple-darwin.tar.gz
- Apple Silicon/arm64:
- Linux
- x86_64:
codex-x86_64-unknown-linux-musl.tar.gz - arm64:
codex-aarch64-unknown-linux-musl.tar.gz
- x86_64:
Each archive contains a single entry with the platform baked into the name (e.g., codex-x86_64-unknown-linux-musl), so you likely want to rename it to codex after extracting it.
Using Codex with your ChatGPT plan
Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. Learn more about what's included in your ChatGPT plan.
You can also use Codex with an API key, but this requires additional setup.
Docs
This repository is licensed under the Apache-2.0 License.