Codex CLI vs Claude Code vs Gemini CLI: which coding agent fits which task?

The first question when choosing a coding agent should not be "which one is strongest?" It should be what you can safely delegate today: a controlled edit in an existing repository, a long refactor, or a research-heavy change across a large context.

This is not a new benchmark. It compares the surfaces described in the vendors’ own documentation, so the capabilities below are vendor claims, not results from a test I ran. I separate model choice in the GPT-5.6 Sol–Terra–Luna guide from the agent shell and permissions here.

Short answer: start with Codex CLI if you want a local repository workflow with file edits, commands and change review. Claude Code fits people who want model selection to stay visible while working through longer tasks. Gemini CLI is worth considering if you want Google Search grounding, web fetching and a large-context workflow in the terminal. These are fit recommendations, not a ranking. [1][2][3]

### Choose by task

Small, clear task: add a test, change an API call, fix a lint error. Use lower reasoning and keep the approval loop tight. Ask for a short plan, inspect the diff, then run the test. OpenAI’s Codex documentation foregrounds inspecting files, making edits and running tools in a local repository. [1]

Medium refactor: a rename across packages, a migration or a test-structure change. Choose the permission boundary before you choose a model name. Keep write and shell access gated: plan first, then a small commit, then tests. Claude Code supports an alias or a full model name; because aliases resolve by provider and can change over time, pinning a full model name is the safer record for repeatable work. [2]

Large repository or documentation search: narrow the context first, then run the agent. Gemini CLI’s README describes it as an open-source terminal agent and lists Google Search grounding, file operations, shell commands and web fetching as built-in tools. That makes it interesting for combining research and code changes in one session, but outside information should never flow into a patch without review. [3]

### Reasoning and cost

Set reasoning according to the cost of being wrong, not as a permanent maximum. A typo may need speed; a data migration, auth flow or payment path needs slower planning and more checks. A longer reasoning trace does not prove that the patch is correct.

If you use a model alias, record the date and provider. Anthropic says aliases point to the recommended version for a provider and update over time. That is convenient, but a solo builder who wants to reproduce a result months later should record the model version and reasoning setting in the commit message. [2]

### How I would start

If you are building alone, I would not make all three tools daily defaults. Pick one primary agent and one second opinion. Let the primary agent plan and change a small task; use the second tool only to critique the diff, test coverage or risky assumptions. I would not let two agents edit the same file back to back.

Track your settings like product code: model, reasoning level, working directory, network access and automatic approvals should be visible. Treat an expanded shell or network permission as a new security boundary, not merely as a speed setting.

Finish with the seven-step coding-agent output checklist. My minimum bar is simple: read the diff, run the tests, check types and lint, try one manual scenario for critical behavior, then commit. An agent saying "done" is only text output.

Bottom line: Codex CLI is a sensible starting surface for controlled repository work; Claude Code is worth a look if you want model and provider behavior to stay explicit; Gemini CLI fits people who want search and web tools alongside terminal work. Choose by the cost of the task going wrong, not by the tool’s name.

Singrey note: The winner for me is not the agent that does the most in one pass. It is the one that makes its files, assumptions and failure modes visible early enough to correct. Speed is useful in a solo workflow. Catching an irreversible change early is better.