Codex local vs cloud: when to delegate tasks
Codex isn’t limited to your terminal or editor. In 2025, it runs in two environments: local execution on your machine and delegated execution in Codex Cloud. This dual model is deliberate. Some tasks are best kept close to your repo; others benefit from the scale and persistence of the cloud.
In this deep dive, we’ll explore:
- Why Codex introduced cloud delegation
- The strengths and trade-offs of local vs cloud execution
- How context flows between both modes
- Real-world workflows for individuals and teams
- Best practices for choosing the right mode
- Security and compliance considerations
By the end, you’ll know exactly when to stay local and when to push tasks to the cloud.
Why cloud delegation exists
For years, AI coding tools were tied to autocomplete or lightweight chat inside the editor. That works fine for small snippets. But as teams asked AI to run migrations, debug flaky tests, or generate scaffolding, local-only execution became a bottleneck. Machines would freeze or lose context between runs.
Codex Cloud was built to solve this:
- Durability: logs and runs persist across sessions.
- Scalability: heavy refactors or test runs don’t bog down your laptop.
- Collaboration: teammates can review or replay a cloud run.
It doesn’t replace local execution—it complements it.
Local execution: speed, privacy, and control
Running Codex locally keeps everything tight:
- Instant feedback: no network latency, runs in your environment.
- Repo privacy: nothing leaves your machine beyond minimal context.
- Full control: you see exactly what Codex edits and executes.
Local mode shines when:
- You’re doing short, iterative tasks.
- The repo contains sensitive data.
- You want Codex to run alongside your usual scripts (tests, builds, linters).
Example:
codex exec "add a zod validation schema for signupForm.tsx"
The diff applies instantly. You run your tests. Done.
Cloud execution: endurance and persistence
Codex Cloud runs tasks remotely:
- Heavy lifting: migrations, deep refactors, multi-step debugging.
- History: logs and results persist for later review.
- Isolation: risky experiments stay off your main machine.
Use Codex Cloud when:
- A task takes minutes, not seconds.
- You need reproducible logs to share with teammates.
- You’re debugging non-deterministic issues.
- You want to compare multiple strategies side by side.
In VS Code, simply toggle to cloud execution. In CLI, you can flag specific commands.
How context flows between local and cloud
A common worry: will Codex lose track if I switch modes? The answer is no. Context persists:
- Files you open in VS Code inform both local and cloud runs.
- Plans and diffs carry across modes.
- You can start locally, escalate to cloud, then finish locally.
Think of it like pairing with a teammate: sometimes you take the keyboard (local), sometimes they run a heavier task (cloud).
Comparison table
| Aspect | Local Execution | Cloud Delegation |
|---|---|---|
| Speed | Instant, CPU-bound | Slight startup cost, scales well |
| Privacy | Repo stays on your machine | Requires remote processing |
| Persistence | No built-in history | Logs saved across sessions |
| Best for | Iterative, short tasks | Long, heavy, collaborative |
| Security | Limited to your system | Requires scoped authentication |
Real-world workflows
Local-first coding
- Use Codex to generate a patch.
- Run your test suite locally.
- Commit if green.
Cloud for flaky debugging
- Delegate a failing test suite to Codex Cloud.
- Review logs in VS Code.
- Iterate until the root cause is isolated.
Hybrid workflow
- Start locally to explore options.
- Switch to cloud for long runs.
- Return local for validation and commits.
Team onboarding
- New developer joins.
- Use Codex Cloud to generate setup scripts and logs.
- Teammates review runs asynchronously.
Performance tuning
- Profile locally.
- Delegate optimization experiments to Codex Cloud.
- Compare strategies with persistent logs.
Best practices
- Default to local. It’s faster and safer for routine work.
- Escalate to cloud when you hit scale or endurance limits.
- Document why. Treat cloud runs like CI jobs: note intent and results.
- Audit configs. Set sensible defaults in
~/.codex/config.toml. - Review everything. Whether local or cloud, always check diffs.
Security and compliance
Codex Cloud is designed with enterprise use in mind, but you still need hygiene:
- Scope authentication tightly (repo-level, not org-wide).
- Never paste secrets into prompts.
- Treat cloud runs like any remote build system.
- For GDPR or compliance-heavy industries, confirm Codex Cloud region settings.
Troubleshooting
- Cloud runs feel slow: network latency + task complexity. Keep small tasks local.
- Lost context: re-open files or add explicit paths to prompts.
- Accidental cloud usage: check defaults in config.
- Permission errors: re-authenticate with correct scopes.
How this fits in the Codex ecosystem
Local and cloud are two halves of the same workflow:
- The VS Code extension guide shows how to toggle execution modes.
- The approval modes guide explains how trust levels apply across local and cloud.
- The complete integration guide ties it all together.
With these pieces combined, you control where Codex runs, how much autonomy it has, and how tasks persist.
Conclusion
Codex isn’t just an assistant—it’s a workflow engine. The choice between local and cloud isn’t binary, it’s situational:
- Stay local for speed, privacy, and iterative dev.
- Go cloud for heavy, collaborative, or persistent runs.
Switching strategically makes Codex safer, faster, and more useful for real teams. The result: AI assistance that works at both the speed of your laptop and the scale of the cloud.
