OpenAI Codex can now be used in several ways. Alongside the Codex desktop app, there's still the Codex CLI for the terminal and the Codex IDE extension for development environments such as Visual Studio Code, Cursor, or Windsurf.
That raises a very practical question: which Codex variant should you actually use?
The short answer:
- IDE extension: ideal for developers who want to work with Codex directly while coding.
- Codex CLI: ideal for terminal users, Linux administrators, DevOps, and extensive repository work.
- Codex app: ideal for larger projects, parallel agents, worktrees, automations, and centrally managing multiple tasks.
These aren't three completely different AI systems. OpenAI positions Codex as the same coding agent, usable across ChatGPT, the editor, and the terminal.
Which interface works best therefore depends less on the underlying model and more on your own workflow.
What exactly is OpenAI Codex?
Codex is an agentic coding assistant from OpenAI. Unlike classic code completion, Codex isn't meant to just suggest individual functions or lines of code. The agent can, for example:
- analyze existing projects,
- implement new features,
- find and fix bugs,
- create and run tests,
- carry out refactorings,
- prepare migrations,
- modify files,
- run shell commands,
- prepare pull requests,
- perform code reviews,
- work through larger tasks across multiple steps.
OpenAI now explicitly describes Codex as a coding agent for complete development tasks — from smaller pull requests to larger refactorings and migrations.
The key question is no longer just "Can Codex write this code?" It's increasingly "Through which interface can I steer Codex most effectively for this task?" That's exactly where the app, CLI, and IDE differ.
Codex App, CLI, and IDE compared directly
| Property | Codex App | Codex CLI | Codex IDE |
|---|---|---|---|
| Interface | Graphical desktop app | Terminal | Directly in the editor |
| Getting started | Very easy | More technical | Easy |
| Small code changes | Good | Good | Very good |
| Large repository tasks | Very good | Very good | Good |
| Terminal workflows | Good | Very good | Good |
| Multiple agents in parallel | Very good | Possible, but less convenient | Not the main focus |
| Worktrees | Built in | Git-/terminal-oriented | Depends on the editor |
| Editing code directly | Via editor handoff | Via files/terminal | Very good |
| Reviewing diffs | Very convenient | Terminal-oriented | Very convenient |
| Linux server/SSH | Not the primary use case | Very good | Depends on the editor |
| Automations | Very good | Good for scriptable workflows | Less central |
| Beginner friendliness | Very high | Medium | High |
| DevOps/sysadmin work | Good | Very good | Good |
| Focus | Orchestration | Terminal & control | Coding |
The three variants compete with each other less than you might first assume. In many professional workflows, they actually complement one another.
1. Codex App: The command center for AI agents
The Codex app takes a different approach than classic coding assistants. It's not meant to be just a chat window next to your code. OpenAI describes the app as a "command center for agents" — a central interface through which developers can manage several Codex agents and tasks at once. That makes the app especially interesting for larger projects.
Working on multiple tasks in parallel
A key feature of the Codex app is separate threads for different tasks. For example, several agents could work simultaneously: one agent analyzes a backend bug, a second creates tests for an API, a third reworks the documentation, and a fourth investigates security issues. The developer doesn't have to wait for task 1 to finish before starting task 2. This parallel way of working is exactly what the app was built for.
Built-in Git worktrees
Support for Git worktrees is especially interesting for professional developers. Multiple agents can work on the same repository at once without constantly altering the same working state. Each agent gets an isolated workspace, which means different implementation approaches can be tried out at the same time. OpenAI explicitly names this worktree support as a central part of the Codex app's multi-agent workflows.
Reviewing changes comfortably
The app shows changes within each agent's thread. Developers can review diffs, leave comments, and then open the changes in their own editor. That creates an interesting division of labor: the Codex app steers the agents, while the IDE is used for manual code editing. For larger projects in particular, this separation can be far more manageable than a single long agent chat.
Automations
Another major difference is automation. Within the app, Codex can run recurring tasks on a defined schedule. OpenAI mentions examples such as issue triage, CI failure summaries, release briefings, and regular bug checks. That moves Codex well beyond classic code generation.
The Codex app is particularly well suited for development teams, large projects, multi-agent workflows, parallel tasks, code reviews, large-scale refactorings, and recurring development tasks.
2. Codex CLI: Codex directly in the terminal
For administrators, DevOps engineers, and developers with a strong terminal workflow, Codex CLI is often the most interesting variant. The CLI runs directly on your own machine and is started from the terminal. OpenAI describes it as a local coding agent for the command line. That brings a decisive advantage: Codex sits exactly where a lot of technical work already happens.
Codex understands the repository
If you start Codex inside a project directory, the agent can analyze the existing files and project structure. Instead of copying individual files into a chat, the task could be:
"Analyze this repository and find possible reasons why the application no longer starts after the last update."
Codex can then inspect project files and prepare changes. For large repositories, that's considerably more practical than classic copy-and-paste into a chat window.
Especially useful for Linux and DevOps
Terminal-based work is already part of daily life for many administrators — think git status, docker compose ps, systemctl status nginx, journalctl -u nginx, pytest, npm test, terraform plan, or ansible-playbook. A CLI-based AI fits very naturally into workflows like these. Codex CLI is especially interesting for Linux administration, Docker, Kubernetes, infrastructure as code, Git, CI/CD, shell scripts, backend projects, and server-side development work.
Installing Codex CLI
OpenAI provides installation scripts for macOS, Linux, and Windows. Alternatively, Codex can also be installed via npm:
npm install -g @openai/codexCodex is then started with:
codexAlternatively, there's an official installer script for macOS and Linux:
curl -fsSL https://chatgpt.com/codex/install.sh | shA dedicated installer is also available for Windows. A detailed step-by-step guide covering sign-in, AGENTS.md, permissions, MCP, and automation is available in Install and Use Codex CLI on Linux (Read article).
Where's the downside of the CLI?
Its biggest strength is also its biggest drawback: you work in the terminal. For experienced developers and administrators that's often ideal. If you'd rather navigate files visually, compare changes directly, and edit specific code sections, the IDE extension usually feels more comfortable. And if you want to monitor ten different agents at once, the Codex app gives you the clearer overview.
3. Codex IDE: AI right where the code is written
The third option is the Codex IDE extension. OpenAI supports Codex directly in Visual Studio Code and compatible editors such as Cursor and Windsurf. OpenAI also offers its own native integrations for Xcode and for JetBrains IDEs like IntelliJ, PyCharm, or WebStorm, where Codex is activated directly through each environment's built-in AI assistant. The basic idea is simple: developers don't have to leave their development environment. That's a big advantage, especially for daily coding work.
Ideal for small and medium changes
Say you're working on a React component. Instead of opening the project in another application or switching to a terminal, Codex can be used directly in the editor. Typical tasks would be: "Check this component for possible bugs.", "Extract the API calls into their own service." or "Write unit tests for this function." The strength of the IDE lies in the immediate switch between AI and manual coding: Codex makes a change, the developer reviews it, and then continues working manually. That fast cycle is what makes the IDE integration especially productive.
Less context switching
A frequently underestimated factor with AI tools is context switching. Constantly moving between browser, terminal, chat, and IDE costs time. With an integrated Codex extension, your workspace stays largely unchanged. Editor, project structure, Git changes, and AI all live within the same workflow.
Which IDEs are supported?
The Codex extension works with VS Code and many VS Code-based development environments, including Visual Studio Code, Cursor, and Windsurf. If you use a different development environment, you still don't have to go without Codex entirely: OpenAI notes that Codex CLI can simply be started inside that IDE's integrated terminal as well.
Codex app or IDE: Where's the key difference?
At first glance, the app and the IDE look similar — both have a graphical interface. But their focus differs. The IDE extension works around the code you're currently editing. The Codex app works around tasks and agents. That's an important distinction.
If you're building a feature right now and need AI support for it, the IDE is usually faster. If you instead want to delegate three features, two bug fixes, and a refactoring to different agents at the same time, the app is far more useful.
Put another way: IDE = pair programming with Codex, app = an agent team with Codex.
Codex CLI or IDE: Which is better?
Again, there's no clear winner. A frontend developer who spends eight hours a day in VS Code will likely prefer the IDE. A Linux administrator working over SSH and inspecting config files, logs, Docker containers, and Git repositories will probably work much faster with the CLI.
The CLI also offers a decisive psychological advantage: you treat Codex like just another Unix tool. Open a terminal, switch to the project, start Codex, state the task. That fits naturally into existing technical workflows.
Codex app or CLI: Which variant is more capable?
That's really the wrong question. The interface doesn't automatically determine the agent's intelligence. OpenAI explicitly follows the approach of making the same Codex agent available across different surfaces. The difference lies mainly in control: the CLI is extremely direct, while the app offers better orchestration.
Interestingly, the Codex app can pick up session history and configuration from the CLI and IDE. That means the different ways of working can be combined — you don't have to commit permanently to a single interface.
The likely best workflow: combining app, CLI, and IDE
For professional users, this combination is probably the most interesting option long term. An example:
Step 1: Planning via the Codex app. A larger feature is first delegated to one agent, a second agent analyzes possible side effects, and a third creates tests.
Step 2: Technical work via the CLI. Codex is used in the terminal for repository analysis, build processes, tests, or infrastructure work.
Step 3: Fine-tuning in the IDE. The generated changes are reviewed in the editor and then refined manually.
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Which Codex variant fits system administrators?
For administrators, I'd consider Codex CLI the primary entry point. The reason is simple: administration work already happens mostly on the command line. Examples include Linux configuration, Docker troubleshooting, log analysis, Ansible, Kubernetes, Git, shell scripts, or infrastructure as code. Codex CLI fits very naturally into existing processes here.
The Codex app becomes interesting once several larger tasks need to be handled in parallel. The IDE is worthwhile especially when administrators regularly build their own tools, Python scripts, APIs, or larger automation projects.
Which variant fits software developers?
For classic software development, the IDE extension is usually the best daily entry point. It minimizes context switching and sits right next to the code.
For larger tasks, though, the IDE shouldn't be viewed in isolation. For refactoring entire projects, running parallel agents, or longer-running development tasks, the Codex app offers considerably more overview. The CLI remains interesting at the same time for tests, build processes, repository work, and developers who simply prefer working in the terminal.
Which variant fits beginners?
Here the Codex app is likely the most accessible. Its graphical interface makes agents, projects, and changes visible. CLI commands or terminal skills matter less.
If you already work in VS Code, though, you'll likely get up to speed with the IDE extension very quickly too. The CLI has the steepest learning curve — but in exchange offers technically skilled users the most control.
Security: Codex shouldn't simply be allowed to do everything
Regardless of the interface, a coding agent should never get uncontrolled access to production systems. Production servers, databases, API keys, cloud accounts, Kubernetes clusters, deployment systems, and CI/CD secrets are especially critical.
OpenAI relies on sandbox and permission mechanisms for the Codex app and CLI. Actions requiring elevated permissions can require additional approval. For a detailed walkthrough of sandbox modes, Git worktrees, backups, and approvals, see How to Use OpenAI Codex Safely: Git, Sandbox, Backups, and Approvals (Read article).
Still, a coding agent is no substitute for a proper permissions concept. Git, backups, separate development environments, code reviews, and least privilege remain essential even with AI in the loop.
Which Codex variant should I choose?
If you only want to try one variant, a simple rule can help:
- You mainly code in VS Code, Cursor, or Windsurf? → Start with the Codex IDE extension.
- You mainly work with Linux, Git, Docker, shell, or DevOps tools? → Start with Codex CLI.
- You want to coordinate several larger tasks or agents at once? → Use the Codex app.
- You work with Codex professionally and regularly? → Combine all three variants.
Conclusion: Not app or CLI or IDE — the right tool for the task
The debate over Codex app vs. Codex CLI vs. IDE has no clear winner — and that's probably by design. OpenAI is increasingly building Codex as an agent platform that works independently of any single user interface.
The IDE extension excels at daily work directly on the code. The CLI is especially strong for terminal, Linux, DevOps, and repository workflows. The Codex app plays to its strengths when multiple agents, projects, or long-running tasks need to be coordinated.
For many professional users, picking a single variant probably isn't the best approach. The most productive workflow likely emerges when Codex is used wherever each interface is strongest: IDE for coding, CLI for working, app for orchestrating. And that's really the core advantage of Codex's current design.
For more general professional tasks outside of software development — research, documents, spreadsheets, and workflows — ChatGPT Work has taken on that role. See ChatGPT Work Explained: How to Tackle Bigger Tasks with ChatGPT in 2026 (Read article) for what Work can do and how it differs from Codex.
Frequently asked questions about Codex App, CLI, and IDE
Is the Codex app better than Codex CLI?
Not fundamentally. The app is more convenient for parallel agents and larger workflows. The CLI is especially well suited to terminal, Linux, DevOps, and repository work.
Is Codex CLI free?
As of September 2026, Codex is available across ChatGPT plans. Usage limits vary depending on the plan.
Can I use Codex on Linux?
Yes. Codex CLI supports Linux and can be used directly from the terminal.
Is the Codex app available for Windows?
Yes. OpenAI first released the Codex app for macOS in February 2026 and made it available for Windows on March 4, 2026.
Does Codex work with VS Code?
Yes. Codex is available as an extension in Visual Studio Code and VS Code-based editors such as Cursor and Windsurf. OpenAI also offers native integrations for Xcode and JetBrains IDEs like IntelliJ, PyCharm, or WebStorm.
Can I use Codex with other IDEs?
Yes. If no native or compatible Codex extension is available, Codex CLI can simply be started inside that IDE's integrated terminal.
Can I use the Codex app and CLI at the same time?
Yes. The interfaces are not designed as isolated products. The Codex app can, among other things, pick up existing session history and configuration from the CLI and IDE.
Which Codex variant is best for developers?
For daily coding work, the IDE extension is usually the best fit. For larger repository tasks and terminal-heavy workflows, the CLI is interesting. For multi-agent workflows and parallel tasks, the Codex app offers the most comfort.
Sources and further reading
The product information in this article is based on current official information from OpenAI and the official OpenAI Codex repository, as of September 11, 2026: the official Codex CLI documentation, the Codex IDE documentation, and OpenAI's "Introducing the Codex app" announcement.
Related topics and sources
Install and Use Codex CLI on Linux (Read article)
How to Use OpenAI Codex Safely: Git, Sandbox, Backups, and Approvals (Read article)
Claude Code vs. OpenAI Codex: Which Coding Agent Is Better? (Read article)