Codex Desktop vs CLI vs Web: Which Fits Your Workflow?

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The same Codex workflow can look drastically different for developers. Some users dispatch long-running cloud tasks through the web interface, others perform local diff reviews on the desktop client, and many run code modifications directly inside their terminal shell. These are not three separate independent products. They represent three distinct execution surfaces: the web interface primarily targets ChatGPT Projects and Codex Cloud; the desktop client unifies local files, Git worktrees and cloud environments into one workspace; the CLI runs operations directly from the active terminal directory. All information in this guide is validated against official documentation current as of October 22, 2026.

Clarify the Three Entry Points First

The core distinction between Codex’s three clients lies in where code and tasks execute, not the visual layout of each interface. The table below summarizes default runtime locations, suitable workloads and hard operational boundaries.

Official documentation lists desktop, ChatGPT Web, Codex CLI and Codex Cloud as separate access channels. Web, mobile and desktop clients can all start or resume Cloud tasks. This capability does not mean local files, terminal sessions or browser login states automatically synchronize cross-platform. Developers must explicitly understand the isolation rules before switching clients mid-task.

Desktop Client: Manage Three Workspace Modes Within One Window

The desktop client suits developers who need concurrent visibility over project files, browser resources and live task status. Official desktop installers are available for macOS, Windows and Linux. After login, users can create projects, open local folders, and select Codex from the ChatGPT dropdown menu.

Once inside Codex, the desktop client exposes three separate execution modes:

1. Local: Reads and writes files directly within the active project directory. This mode is ideal for small iterative edits, local debugging and invoking native machine tooling.
2. Worktree: Isolates a task inside a dedicated Git worktree. Developers use this mode for experimental refactors, parallel branch development, or risky changes that must not pollute the primary working tree.
3. Cloud: Offloads the task to a pre-provisioned remote cloud runtime. This is designed for long-running jobs, parallel remote execution and workflows that persist when the local machine sleeps.

A desktop local project can attach one or more nested folders. The root folder you select defines the default working directory, and controls where Codex discovers AGENTS.md, skill definitions and config.toml configuration files. Selecting the repository root as your primary folder yields more consistent instruction parsing than opening only a nested subdirectory.

The most frequently overlooked pitfall is mode switching. Seeing the Cloud label does not confirm your local source files have been uploaded. Seeing Worktree mode does not guarantee the task runs remotely. Before making code changes, always verify your active mode and working directory to avoid unintended edits in the wrong environment.

CLI: Embed Codex Directly Into Your Native Development Loop

Codex CLI targets local git repositories. Developers use it inside terminals to inspect source code, edit files, run shell commands, and integrate Codex logic into scripts or continuous pipelines via codex exec.

Installation and Authentication

Official documentation provides four installation pathways, select one matching your operating system:

# macOS / Linux
curl -fsSL https://chatgpt.com/codex/install.sh | sh

# NPM global install
npm install -g @openai/codex

# Homebrew
brew install --cask codex

Windows PowerShell installation command:

powershell -ExecutionPolicy ByPass -c "irm https://chatgpt.com/codex/install.ps1 | iex"

After installation, navigate into your repository folder and launch Codex with the simple codex command. On first launch, you may select “Sign in with ChatGPT” or other available authentication flows. The CLI also supports explicitly defining your target project directory:

codex -C /path/to/repository

For API key-based login, use this command:

printenv OPENAI_API_KEY | codex login --with-api-key

Run codex login status to inspect your current authentication method, and codex logout to clear stored credentials. API key authentication follows standard OpenAI API billing rules. Note that some features dependent on ChatGPT workspaces or Cloud environments may be unavailable with key-only login. For workflows requiring Codex Cloud, authenticate via ChatGPT account login.

Four High-Frequency CLI Operations

These are the most commonly used interactive and non-interactive commands for day-to-day development:

# Interactive development session
codex

# Non-interactive execution, for scripts and CI pipelines
codex exec "run test suite and summarize failure reasons"

# Resume or reconnect to an existing session
codex resume

# Audit and review local changes
codex review

The CLI includes additional flags and subcommands: codex --image passes screenshots or architecture diagrams as context, codex --search runs contextual searches over project content, codex cloud sends work to remote cloud runtimes, and codex mcp manages MCP server connections. A consistent local workflow pattern is to check git status first, allow Codex to apply changes, then validate and accept edits with git diff.

Web Interface: Research and Dispatch Cloud Tasks

The web interface is built for initiating work from a browser, especially tasks requiring reference materials, project context or remote infrastructure. ChatGPT Web Projects share conversation history, attached files and project documentation. It works with uploaded or linked source artifacts and cannot directly read local files stored on your workstation.

When a workflow requires access to a GitHub repository, the primary web pathway is Codex Cloud, following these sequential steps:

1. Open Codex within ChatGPT web, enter Cloud mode and select your target environment.
2. Connect your GitHub repository, then trigger initialization. Codex automatically scans dependencies, tooling and test pipelines.
3. Add missing permissions or environment configurations, validate the provisioning checks, and finalize the environment deployment.
4. Create a new task within the ready environment, describe your objective and submit the job.
5. Inspect code changes and test outputs, add follow-up prompts, and submit or open a Pull Request once validation passes.

Each Cloud task runs within its own isolated workspace. Tasks continue processing even after your computer enters sleep mode. This isolated workspace does not automatically import local files, running local processes, browser session states or VPN connections. If your task requires these resources, switch to desktop Local/Worktree mode, or explicitly configure repository access, network rules, environment variables and secrets within the Cloud environment definition.

How The Three Surfaces Hand Off Work, Rather Than Compete Against Each Other

The strongest production workflows use the three clients in sequence, not as mutually exclusive alternatives. A reusable pipeline follows this pattern: define objectives on the web interface and let Cloud run the initial pass, review outputs and adjust scope on desktop, then run final validation and automation locally in CLI.

For a concrete example: adding a webhook payment callback to an existing GitHub repository:

1. Create a Cloud task on the web interface. Let Codex explore repository structure, map dependencies and identify test entry points.
2. Open the identical task on the desktop client. Inspect proposed code edits, review test logs and follow recommendations. Switch to Local or Worktree mode if local file access is required.
3. Move to the CLI within your local branch. Run existing linting rules, unit tests and build commands.
4. Use git diff to audit the change range. Confirm no secrets, generated binaries or malformed artifacts are staged for commit.
5. For repeatable runs, formalize validated steps into reusable codex exec scripts or CLI task definitions.

This handoff workflow depends on clear awareness of where code executes at every stage. Files attached to a web project are not automatically available in your local workspace, and branches inside a Cloud environment do not match your current local git branch. When switching between clients mid-task, always confirm repository, branch, environment and the latest diff state before continuing work.

Selection Guidance: Decide Based On Task Boundaries

• If you need persistent access to local source code, files outside your IDE, or native local tools: use desktop Local mode or CLI.
• If you need isolated experiments, parallel refactoring, or protection for your primary working tree: use desktop Worktree mode.
• If you require remote execution, parallel jobs, or tasks that survive machine sleep: use web or desktop Cloud mode.
• If you need local scripting, CI integration, batch auditing or MCP connections: use CLI, prioritizing codex exec, codex review and codex mcp.
• If you need research, project documentation and non-coding planning work: start in ChatGPT Web Projects, then pass well-defined coding tasks to Codex Cloud.

Only three core rules need to be retained: the CLI project root is its launch directory, desktop Local mode operates on the selected folder, and web Cloud mode spins up independent remote environments. As of the October 2026 documentation release, the three desktop execution modes and this five-step Cloud provisioning flow represent the most stable and documented usage pattern.

All installation routes, authentication variants and environment capabilities are subject to adjustments aligned with the live official documentation.

This article is published by 4sapi, and all command examples and workflow patterns referenced are sourced from OpenAI’s public Codex documentation. Before rolling out Codex to a team, verify that your runtime provider supports the interfaces and authentication flows you intend to adopt.