Codex vs Claude Code vs Gemini CLI (2026)

Three terminal coding agents now do real work in your repo, and picking one feels like picking a side. Claude Code writes the cleanest multi-file changes. Codex is the sharpest reviewer and ships with the best GitHub story. Gemini CLI was the free, high-context option until Google started moving that experience to Antigravity in June 2026. This post compares all three factors that actually determine a workflow: code quality, cost, and context, as well as GitHub integration and MCP. The strongest teams don’t pick one. They route the same task to two or three agents and let the disagreements surface the bugs.

These are different tools with different defaults, so the version details below were checked against each vendor’s docs on June 28, 2026. The model landscape moves fast, and one of the three has changed shape this month.

Quick verdict: which terminal agent wins

If you want one line per tool, here it is.

• Claude Code is the strongest implementer. It reads a repo, plans, and lands multi-file changes with the least hand-holding. Best for refactors, migrations, and “make this work across the codebase” tasks.
• Codex is the strongest reviewer and the most CI-native. The @codex review, GitHub flow, and a per-token API option make it the easiest to wire into pipelines and pull requests.
• Gemini CLI had the most generous free tier and a 1-million-token context window, but as of June 18, 2026, Google moved its consumer and free access to a new tool called Antigravity CLI. The open-source repo and enterprise API access continue.

Who wins depends on the job: deep code generation favors Claude Code, automated PR review favors Codex, and huge-context reads favor Gemini on an enterprise or API plan. None of them wins every category, which is why the “use all three” pattern keeps showing up in developer threads.

Comparison table: code quality, cost, context, GitHub, MCP

Here is the head-to-head on the dimensions developers actually weigh, drawn from each vendor’s official docs.

All three now support MCP and ship a GitHub integration, so the table has converged on the basics. The real separation is in defaults and posture: Claude Code leans into autonomous implementation, Codex leans into review and automation, and Gemini’s terminal story is mid-transition.

Claude Code: the strongest implementer

Claude Code is Anthropic’s terminal agent. The official docs describe it as a tool that “reads your codebase, edits files, runs commands, and integrates with your development tools,” and it runs in the terminal, IDE, desktop app, and browser. It shows up first in most “which one builds the feature” conversations because it does the boring connective work without being told: locating the right files, proposing a sequence, and applying the change across them.

Plan mode is the feature that makes it trustworthy for big tasks. Claude Code exposes an opusplan mode that uses Opus for the reasoning and architecture pass, then switches to Sonnet for execution: the expensive model where judgment matters, and the faster model where it’s just typing. On a migration touching twenty files, that split is the difference between a careful diff and a runaway one.

Model defaults depend on your plan. On Max, Team Premium, Enterprise pay-as-you-go, and the API, Claude Code defaults to Opus 4.8; on Pro, Team Standard, and Enterprise subscription seats, it defaults to Sonnet 5. The newer models (Opus 4.6 and later, Sonnet 4.6, Sonnet 5, and Fable 5) support a 1-million-token context window. On Max and above, Opus is automatically upgraded to the 1M window, which is what lets it hold a large service in context during a refactor instead of summarizing chunks and losing the thread.

For configuration, Claude Code reads a CLAUDE.md file at session start, and the related AGENTS.md convention has become a portable way to give any agent the same project context. The practical catch worth naming: Claude Code is proprietary. There’s no public source repo, so if open-source tooling is a hard requirement, that rules it out before benchmarks come into play.

Codex: the strongest reviewer, with the best GitHub and pricing story

Codex CLI is OpenAI’s terminal agent, and its own docs put it plainly: it’s “open source and built in Rust for speed and efficiency.” That Rust foundation and the Apache-2.0 license make it the one you can actually read, fork, and run in a locked-down environment. Where Claude Code wants to implement, Codex is at its best at catching what the implementation got wrong.

The GitHub review flow is the standout. Once you enable Codex on a repository, it reviews pull requests automatically as they move from draft to ready, and you can trigger a review on demand by commenting @codex review on a PR. That makes it a natural second set of eyes in a pipeline: the agent that wrote the code and the agent that reviews it don’t have to be the same one. Codex also takes image input, so a screenshot of a broken UI or a design spec can go straight into the prompt.

Pricing is where Codex has the most flexibility. The CLI is included with ChatGPT plans, from Free ($0) through Plus ($20) and Pro (from $100 with higher rate limits), so most developers already have access. For automation, run it instead with an OpenAI API key and pay per token: the default gpt-5.5 model bills at $5 per million input tokens and $30 per million output, with prompts over 272K input tokens priced at 2x input and 1.5x output. Use the API key for CI, since OpenAI’s own docs note it drops cloud features like GitHub code review and Slack; use the ChatGPT plan for interactive review.

Gemini CLI: free, fast, biggest context, and now in transition

Gemini CLI is Google’s open-source terminal agent, Apache-2.0-licensed, and for most of the past year, it was the obvious free pick. The README still describes “Gemini 3 models” with a “1M token context window,” and a personal Google account gets you 60 requests per minute and 1,000 requests per day at no cost. For reading an entire mid-sized codebase in one pass, that combination was hard to beat.

That changed this month, and most comparison posts haven’t caught up. On June 18, 2026, Google began transitioning the terminal experience from Gemini CLI to a new tool called Antigravity CLI. Per the official announcement on Google’s blog, on that date “Gemini CLI will stop serving requests for Google AI Pro and Ultra, as well as those using it free of charge,” and “these tiers are now supported via Antigravity CLI.” The same change applies to Gemini CLI used through the Gemini Code Assist IDE extensions and on GitHub.

So is Gemini CLI dead? No, but the access model split. Enterprise access “remains unchanged” for organizations on a Gemini Code Assist Standard or Enterprise license or through Google Cloud, and it stays available via paid API keys. The open-source project also continues: per Google, it “remains available to the community as an Apache 2.0 licensed repository with no changes,” and Antigravity CLI itself is a fresh tool built in Go. If you relied on the free consumer tier, that path now runs through Antigravity CLI. Enterprise and API users keep the same 1M-context terminal agent, and the open-source Gemini CLI repository stays active.

Pricing and usage limits across all three

Pricing gets simpler once you separate the free options from the paid ones.

• Codex is included with every ChatGPT plan, including the free one. The API key option bills per token instead, with no monthly commitment.
• Claude Code ships with paid Claude plans only. Pro includes it in the terminal; Max (5x or 20x more usage) gets you the Opus 4.8 default and the auto-upgraded 1M context window.
• Gemini CLI’s free consumer tier is what changed. Free and consumer Pro/Ultra usage moved to Antigravity CLI on June 18, 2026; paid API keys and enterprise licenses keep working with the original CLI.

If cost is the deciding factor, Codex on a ChatGPT Free or Plus plan is the most accessible entry point right now.

The real insight: use them together for multi-agent review

The most useful pattern from developer threads isn’t “which one wins.” It’s that the agents disagree, and the disagreement is the signal. Route the same task to two or three of them, and the bug that one model confidently introduces is often the bug another model flags on review.

A concrete version of this looks like a relay. Claude Code implements the change because it’s strongest at multi-file work. Codex reviews the resulting diff since a reviewer who didn’t write the code catches mistakes the author rationalizes. A third agent acts as a contrarian sanity check, reading the same spec cold to ask why the approach was chosen at all. You synthesize the three outputs instead of trusting any single one.

Run by hand, this is slow and tab-heavy: copying diffs between terminals, re-pasting context, reconciling three opinions yourself. The pattern scales well as a concept and poorly as a manual process, which is the gap that multi-agent orchestration is meant to close: a coordination layer routes the task, collects the responses, and surfaces conflicts so you can review decisions instead of shuffling text. The same idea drives running Claude Code in parallel across independent tasks rather than waiting on one agent at a time.

Orchestrating all three at org scale, model-agnostic

The multi-agent workflow is powerful for a single developer but unmanageable for a team without tooling. That’s the problem we built Tembo to solve. Instead of choosing Codex, Claude Code, or Gemini, we orchestrate any of them across your repos, in your cloud or self-hosted in your own VPC, with runs that are observable and governable.

The model-agnostic posture is the point. Use Claude Code for the implementation, Codex for the review, whatever comes next when it’s better, and swap agents without rewriting your workflow. Because we’re not tied to a single vendor, a model deprecation or a transition like Gemini’s move to Antigravity becomes a config change, not a migration. The orchestration layer routes a task to the right agent and synthesizes the results, turning the manual multi-reviewer relay from the last section into a repeatable process.

Where this gets concrete is in automations. We run agent work on a schedule or in response to events, with full MCP and integration support and webhook payload access, so an incoming Sentry error can trigger a fix, a new pull request can trigger a review, and a Linear ticket can turn into a coordinated change. A single task can open PRs across multiple repositories at once, which is the kind of cross-repo work that no single CLI handles on its own. For a deeper look at how this directly compares two agents, the Codex vs Claude Code breakdown goes into the two platforms in more detail. In practice, this post helps an individual pick and combine tools, while we operationalize that combination for a team.

Conclusion

The three terminal agents have specialized rather than converged: Claude Code implements, Codex reviews, and Gemini CLI is the high-context option now in mid-transition to Antigravity. On MCP and GitHub support, they’ve reached parity, so the decision comes down to workflow fit.

The most defensible answer is to stop choosing. Try the multi-agent pattern on your next real task: have one agent implement, another review, and compare. To run that across a team without the manual tab-shuffling, start on our free tier, which includes 10 free credits (a one-time grant, not a recurring refresh) on one repository, with the option to top up anytime, or book a demo to see model-agnostic orchestration on your own repos.

Frequently asked questions

Which is better, Codex or Claude Code? For implementing changes across many files, Claude Code is stronger. For reviewing code and wiring into CI/CD, Codex is stronger, helped by its @codex review GitHub flow and a per-token API option. Most teams that use both have Claude Code write and Codex review.

Is Gemini CLI still free in 2026? The free consumer tier changed on June 18, 2026. Google began transitioning free and consumer access to Antigravity CLI; per Google’s announcement, Gemini CLI stopped serving requests for free, Pro, and Ultra consumer use on that date. Enterprise licenses and paid API keys still work, and the open-source repository continues unchanged.

Codex vs Claude Code vs Gemini CLI: which has the biggest context window? They are close. Gemini CLI offers a 1-million-token window, Claude Code’s newer models support up to 1 million tokens (auto-upgraded to 1M for Opus on Max and above), and Codex’s gpt-5.5 documents a roughly 1.05M-token context window (922K input, 128K output), with pricing that steps up 2x/1.5x once a session passes 272K input tokens. Context size is no longer a strong differentiator among the three.

Do all three support MCP? Yes. Claude Code, Codex, and Gemini CLI all support the Model Context Protocol for connecting external tools and context. MCP support has become table stakes for terminal agents.

How do they compare on coding benchmarks? Public SWE-bench numbers for these tools cluster closely and vary by source and version, so treat them as a tiebreaker rather than a deciding factor. The bigger differences are in workflow fit, implementation versus review versus context size, so validate with a real task on your own codebase.

Can I use more than one at the same time? Yes, and many teams do. Routing the same task to two or three agents and comparing outputs catches more bugs than any single agent, though doing it by hand is tedious enough that orchestration platforms exist to route, run, and synthesize multiple agents automatically.