Codex

By OpenAI
AI AssistantUsage-based

Turn plain English into reliable code with OpenAI Codex—your cloud-based software engineering copilot.

Last updated Apr 24, 2026

Claim Tool

What is Codex?

OpenAI Codex is a cloud-based AI coding agent that transforms natural language into production-ready code, automates code reviews, and integrates seamlessly with IDEs, CLIs, and GitHub to accelerate development across multiple programming languages while boosting developer productivity and code quality.

Codex's Top Features

Key capabilities that make Codex stand out.

Automated code generation and modification from natural language prompts

Code understanding and codebase Q&A

Cloud and local execution with stateful handoff between environments

Parallel and proactive task handling in isolated sandboxes

Automated pull request reviews with runnable validation and suggestions

IDE and CLI integration, including a VS Code extension

Secure authentication with multi‑factor support

Pull request creation and proposal automation

Reinforcement learning on real‑world codebases for iterative, instruction‑following behavior

Seamless GitHub repository integration for continuous delivery and faster iteration

Use Cases

Who benefits most from this tool.

Backend engineer

Generate REST endpoints, write unit tests, and fix failing integrations from natural language specs.

Frontend developer

Implement UI components and state management, and modify existing code based on product requirements.

Full‑stack team

Scaffold new projects, configure routing and data models, and set up CI with iterative testing.

Data scientist

Translate exploratory notebooks into production pipelines and optimize performance bottlenecks.

QA engineer

Auto-generate unit, integration, and regression tests and triage failures with explanations.

DevOps engineer

Author CLI scripts and GitHub Actions, validate builds, and automate deployment steps.

Tech lead / Reviewer

Run automated pull request reviews, reason across dependencies, and suggest improvements in PRs.

Project maintainer

Refactor legacy modules safely, rename symbols at scale, and keep style consistent across the codebase.

New team member

Ask questions about the codebase to accelerate onboarding and clarify unfamiliar sections.

Open‑source contributor

Propose and create pull requests directly from issues and natural language prompts.

Explore Top AI Use Cases

Tags

AIcodingcloud-basedproduction-ready codecode reviewsIDEsCLIsGitHubdeveloper productivitymultiple programming languages

Codex's Pricing

Top Codex Alternatives

OpenAI logo
OpenAIai lab

Creating safe AGI that benefits all of humanity

426 Tools6 ModelsFounded 2015San Francisco, CA
View full profile
426 Tools·6 Models

AI Models by OpenAI

Large language models from the same organization.

ModelContext WindowPrice (In / Out per M)
GPT-5.5Current1.1M$5.00 / $30.00
GPT-5.5 ProCurrent1.1M$30.00 / $180.00
GPT-5.4 MiniCurrent400K$0.75 / $4.50
GPT-5.4 NanoCurrent400K$0.20 / $1.25
GPT-5.4Current1.1M$2.50 / $15.00
GPT-5.4 ProCurrent1.1M$30.00 / $180.00

Resources & Guides

Tutorials, guides, and in-depth resources.

OpenAI Codex Quick Start Guide

quickstart

Get Codex running in under 5 minutes. Covers CLI installation on every platform, authentication with ChatGPT or API keys, your first tasks, the desktop app, Codex Cloud, and IDE extensions.

Codex CLI: The Complete Guide

guide

Master Codex CLI: interactive vs exec mode, key flags (--full-auto, --sandbox, --model), config.toml setup, slash commands, and remote WebSocket sessions.

Mastering AGENTS.md: Codex Custom Instructions

guide

Complete guide to AGENTS.md for OpenAI Codex — discovery hierarchy, override files, fallback filenames, /init scaffold, size limits, verification, and troubleshooting.

Codex Skills & Plugins: Extend Your Agent

guide

A comprehensive guide to the Codex Skills and Plugins system - how skills are defined, stored, invoked, bundled into plugins, and configured for OpenAI agents.

User Reviews

Share your thoughts

If you've used this product, share your thoughts with other builders

Recent reviews

Frequently Asked Questions

What is OpenAI Codex?
OpenAI Codex is a cloud-based software engineering agent that can write features, fix bugs, answer questions about your codebase, and propose pull requests from natural language prompts.
Who can access OpenAI Codex?
Codex is available to ChatGPT Pro, Business, and Enterprise users, and is being rolled out to Plus and Edu users.
What programming languages does Codex support?
Codex supports a wide range of popular programming languages, frameworks, and libraries, enabling code generation, refactoring, and understanding across multiple stacks.
How does Codex write and review code?
Powered by the codex-1 model optimized for software engineering and trained via reinforcement learning on real-world tasks, Codex can work in parallel and iteratively test code until it meets specified criteria.
Can Codex help with debugging or optimizing code?
Yes. Codex can fix bugs, explain complex logic, and refactor and optimize code to improve efficiency and maintainability while preserving intended behavior.
Is Codex available in my preferred development environment?
Yes. Codex integrates via a CLI and a VS Code extension and can also be used from an IDE terminal, making it compatible with many development setups.
Does OpenAI use my code or prompts submitted to Codex for model training?
For Business, Enterprise, and Edu users, OpenAI does not use inputs or outputs from Codex by default to improve models. Pro and Plus users can disable training in ChatGPT data controls.
Can Codex automate repetitive engineering tasks?
Yes. Codex can automate tasks such as writing tests, renaming, refactoring, and scaffolding projects so developers can focus on higher‑value work.
What are the “Insert” and “Edit” capabilities of Codex?
Insert and Edit let you add contextually relevant text within existing code or modify code based on instructions, making updates and refactors efficient.
How do I get started with Codex?
Review the Codex Overview documentation, explore best practices, and use the built‑in guides to integrate Codex for code generation, understanding, and optimization.