Cursor vs Claude Code vs Codex CLI vs Gemini CLI

By May 2026, "AI coding agent" stopped meaning "chatbot in a sidebar." The category split into two surfaces — the in-IDE editor and the terminal — and four vendors now own the top of the market. Cursor Composer, Claude Code CLI, OpenAI Codex CLI, and Gemini CLI all do real autonomous work: they plan across multiple files, execute commands, run tests, and ship diffs you review. But the workflows they reward are wildly different.

This piece compares them head-to-head on setup, agent depth, MCP and tool support, model picker, pricing, and the workflows each one wins.

How do Cursor Composer, Claude Code, Codex CLI, and Gemini CLI compare at a glance?

All four are agentic — they plan, execute, and iterate. The differences show up in surface, default model, ecosystem, and how much they cost when you actually use them all day.

That table hides the actual workflow gap. The next four sections unpack each tool individually.

What makes Cursor Composer different?

Cursor is a VS Code fork with AI plumbed through every surface — tab completion, inline edit, chat, and the Composer agent. Composer 2.5, released May 18, 2026, is Cursor's proprietary agentic coding model (built on Kimi K2.5 and post-trained in-house). It scores 79.8% on SWE-Bench Multilingual and 69.3% on Terminal-Bench 2.0. Both figures are Cursor's own, published at launch in May 2026.

This paragraph used to add that Composer 2.5 landed third on Artificial Analysis's Coding Agent Index with a composite score of 63. That claim is gone, not corrected: Artificial Analysis retired its standalone Coding Agent, Coding and Agentic indices into a single Intelligence Index, and rebased that composite to v4.3.2 in October 2026 with no published conversion from the older v4.1.1 scores. Cursor's Composer models are not individually listed on Artificial Analysis either, so there is no current third-party composite to quote for Composer at all. For calibration on the models Composer competes with, Artificial Analysis v4.3.2 (October 2026) puts Claude Opus 4.7 (Max) at 40.69 and GPT-5.5 (Xhigh) at 38.36 — and their successors well above both, at Claude Opus 5.5 (Max) at 57.62 and GPT-6 Astra (Max) at 52.67. Always carry the effort tier with the number: Artificial Analysis's unqualified labels do not map to a consistent tier across vendors, so an untiered score is not comparable to another untiered score.

Setup

Download the installer from cursor.com, sign in, point it at your repo. There's no terminal install, no Node version dance. The editor is the agent — and that's the point.

Agent capabilities

Composer is the multi-file editor. Describe a change in plain English ("add JWT auth to all API routes with refresh token rotation") and it modifies route handlers, middleware, schemas, env vars, and tests in a single coordinated diff. Agent mode plans and executes autonomously. The February 2026 parallel-agents update lets up to eight agents run simultaneously on separate git worktrees, so you can dispatch a refactor, a test-gen task, and a docs-update in parallel without colliding.

Model picker and MCP

The model dropdown spans Composer 2.5, Claude Opus 4.7, GPT-5.5, Gemini 2.5 Pro, DeepSeek V4, and Auto. Auto is unlimited; specific frontier models draw from a monthly credit pool. MCP support landed in early 2026 — you can wire in custom tool servers for databases, internal APIs, or anything else, though the catalog is smaller than Claude Code's.

Pricing

Hobby (free, limited requests), Pro ($20/mo with $20 credits and unlimited tab completions), Pro+ ($60/mo, 3x credits + background agents), Ultra ($200/mo, 20x usage), Teams ($40/user/mo). Annual billing saves 20%.

What makes Claude Code CLI different?

Claude Code is Anthropic's terminal-native execution agent. You type a goal, it reads your codebase, plans across files, edits, runs tests, commits, and iterates on failures. Sessions get isolated git-worktree copies so parallel agents don't trample each other. The April 14, 2026 redesign added a dedicated desktop app built around parallel agentic work — not a wrapper around the terminal, a separate environment.

Setup

npm install -g @anthropic-ai/claude-code, then claude in any directory. Sign in with your Anthropic account. Native VS Code, Cursor, Windsurf, and JetBrains extensions exist if you want it inside an IDE.

Agent capabilities

Claude Code's strength is execution depth. When CI fails, it reads the logs, fixes the code, and re-runs the suite. It monitors GitHub Actions and GitLab pipelines. It composes via Unix philosophy — pipe logs in, chain it with other tools, run it in CI. The 128K output token limit (double Gemini's and Codex's) matters for large refactors where the diff itself is huge.

Model picker and MCP

Sonnet 4.6 for fast iterations, Opus 4.7 for hard problems. Opus 4.7 carries the full 1M context window at standard pricing — no premium tier, no beta header. A 900K-token request costs the same per-token rate as a 9K one, which changes how you scope a session. MCP is native: Anthropic created the protocol, and the server ecosystem (databases, monitoring tools, internal docs) is the most mature of any agent.

Pricing

Pro $20/mo (both Sonnet and Opus), Max 5x $100/mo, Max 20x $200/mo. Token quotas reset on a 5-hour rolling window plus a weekly cap. A June 15, 2026 change separates interactive Claude Code from programmatic SDK use — automated workflows move to an Agent SDK credit billed at API list prices, so scripted CI runs should price accordingly.

What makes OpenAI Codex CLI different?

Codex CLI is OpenAI's terminal agent, rebuilt in Rust in early 2026 for a noticeable speed bump on startup and token processing. It runs locally, reads and edits files in the selected directory, and now reads the integrated terminal for the current thread — so it can check the status of your dev server or refer back to a failed build while it works.

Setup

npm install -g @openai/codex (or grab the Rust binary release), then codex. Sign in with your ChatGPT account; the free tier is generous enough to get real work done before you upgrade.

Agent capabilities

Goal mode is now generally available — Codex drives toward a specific objective for hours or even days, across the CLI, IDE extension, and Codex app. Subagents parallelize complex tasks. You can attach screenshots or design specs and have it generate or edit images directly in the CLI, which is useful when iterating on UI from a Figma export. Terminal-Bench 2.0 puts Codex at 82.0% versus Claude Code's 69.4% — Codex CLI handles terminal-native tasks (file ops, shell scripting, git surgery) more reliably.

Model picker and MCP

The /model command switches between GPT-5.5, GPT-5.4, GPT-5.3-Codex, and reasoning-level variants. GPT-5.5 leads SWE-bench Verified at 88.7%, a small but real edge over Opus 4.7's 87.6%. MCP support is full — you can plug in any MCP server. In Codex Desktop, GPT-5.5 is capped at 272K input tokens (400K total context with 128K reserved for output). Long-context pricing applies for prompts above 272K input ($10/M input, $45/M output), so heavy-context sessions cost more than the equivalent Claude Code session on Opus 4.7's flat 1M tier.

Pricing

Go ($8/mo), Plus ($20/mo), Pro ($100/mo for 5x Plus + GPT-5.5 Pro), Pro ($200/mo for 20x limits). At equal $20/mo plans, Codex tends to deliver more per-task because of roughly 3-4x lower token consumption per workflow versus Claude Code — though that gap depends heavily on how chatty the agent is configured to be.

What makes Gemini CLI different?

Gemini CLI is Google's open-source terminal agent, Apache 2.0 licensed. It uses a ReAct (reason and act) loop with built-in tools — Google Search grounding, file ops, shell commands, web fetch — plus MCP for custom integrations. The free tier is the most generous in the category and remains so: 60 requests per minute and 1,000 requests per day on a personal Google account, now served by Gemini 3 as a mix of Flash and Pro, with a megatoken context window.

It is also the most actively developed of the four in the open. The repository carries 107,000+ stars, shipped stable release v0.62.0 on 29 September 2026, and has nightly builds landing daily — v0.64.0 nightlies as of 5 October 2026. There is no deprecation notice, no sunset date and no migration path published in either the README or the releases page.

That last point needs saying plainly, because this page got it wrong. The May 2026 version reported that Gemini CLI would be replaced by Antigravity CLI on 18 June 2026 and that free, Pro and Ultra users would lose access. The shutdown never happened. Gemini CLI is alive, open, free at the same quotas, and on a faster release cadence than it was in May.

One configuration detail trips up teams running several agents side by side: Gemini CLI reads GEMINI.md, not AGENTS.md. If your repo standardised on AGENTS.md for Codex and other agents, Gemini CLI will silently ignore it until you tell it otherwise. The fix is the context.fileName setting in settings.json, which accepts a string or an array — Google's own documented example is:

{
  "context": {
    "fileName": ["AGENTS.md", "CONTEXT.md", "GEMINI.md"]
  }
}

Context files load hierarchically: ~/.gemini/GEMINI.md globally, then workspace files and their parents, then just-in-time discovery when a tool touches a directory. The footer shows how many are loaded, which is the quickest way to confirm your rename actually took.

Setup

npm install -g @google/gemini-cli, then gemini. Sign in with a Google account for the free OAuth quota, or set an API key. Pin a model with gemini -m gemini-3.8-flash if you do not want the default Flash/Pro routing.

Agent capabilities

Standard agentic flow — plans, executes, iterates. Strong at code understanding and shell command chaining thanks to Google Search grounding, which lets the agent verify API docs in-flight without an MCP server. The repo now documents subagents, git-worktree sessions, plan mode, checkpointing and rewind, a sandbox, agent skills, hooks, and a policy engine, so the feature surface has closed most of the gap on the commercial agents since May. Being Apache 2.0 is the structural differentiator: it is the only one of the four you can read, fork, and run against your own endpoint.

Pricing

Free on a personal Google account: 60 requests per minute and 1,000 requests per day, served by Gemini 3 as a mix of Flash and Pro. An API key gets you the same 1,000/day figure and lets you pin a specific model and pay per token beyond the quota. Enterprise Gemini Code Assist starts around $19–25/user/month and is where you go for admin controls, not for raw capability. There is no paid Gemini CLI tier to buy — the CLI is free software and you pay Google for model access, not for the agent.

Which tool should you use for which workflow?

The honest answer is: most working engineers in 2026 use two of these together. Here's how the workflows shake out.

Choose Cursor Composer if...

• You think in panes, diffs, and inline edits. The editor IS the workflow.
• You do a lot of UI iteration where a live browser preview and tab completion matter more than autonomous depth.
• You want a single tool that handles tab completion, inline edits, and agent work — switching context costs you focus.
• You're an IC doing daily feature work, not architectural refactors.

Choose Claude Code CLI if...

• Your work involves large interconnected codebases — architectural refactors, cross-service debugging, multi-day migrations.
• You want flat 1M-context pricing without per-token premium tiers kicking in.
• You're heavy on MCP — connecting to databases, internal APIs, custom tool servers.
• You delegate big tasks and review later ("senior-engineer dispatch" workflow).
• You care about output token capacity (128K) because your diffs are huge.

Choose OpenAI Codex CLI if...

• You run hundreds of agent jobs per day in CI and per-token cost dominates your decision.
• You do a lot of terminal-native work — shell scripts, git surgery, file ops — where the 82.0% Terminal-Bench 2.0 score actually matters.
• You want the SWE-bench leader (GPT-5.5 at 88.7%) and you're willing to manage long-context billing.
• You want subagents and a long-running goal mode (hours-to-days).
• You already pay for ChatGPT and the free Codex tier is enough to get going.

Choose Gemini CLI if...

• You need a genuinely free agent for personal projects, side work, or learning. 1,000 requests a day with no credit card is unmatched in this group.
• You need the agent to be auditable or self-hosted against your own endpoint — it is the only Apache 2.0 option of the four.
• Your org already pays for Google Workspace and Gemini Code Assist Enterprise is in the contract.
• Your work benefits from live Google Search grounding as a first-class built-in tool rather than an MCP server you have to wire up.
• You want a megatoken context window without a per-token premium tier.

What's the common pairing pattern?

The most effective 2026 setup pairs an IDE-resident editor with a terminal-resident execution agent. Cursor Composer for tight inline work, Claude Code CLI dispatched in a second pane for autonomous refactors. The two coexist cleanly — Cursor even ships a Claude Code extension. Codex CLI slots in as the CI-side agent because of its token efficiency.

A working engineer's day might look like this: tab completion and inline edits in Cursor for 70% of work, a Claude Code session dispatched in a terminal for the one big refactor that needs to span eight files, and a Codex CLI job triggered from GitHub Actions to keep the test suite green overnight. Three agents, three surfaces, one engineer.

How do these agents handle MCP and custom tools?

Model Context Protocol — Anthropic's open standard for AI-to-tool connections — is now the lingua franca. All four agents support it, but maturity varies.

Claude Code has the deepest ecosystem because Anthropic invented MCP. Hundreds of pre-built servers exist for databases (Postgres, MySQL, Redis), monitoring (Sentry, Datadog), docs systems (Notion, Confluence), and dev infra (GitHub, Linear, Jira). The hook system is its own differentiator — you can intercept agent decisions at custom checkpoints.

Cursor added MCP in February 2026. The catalog is smaller but the UX of attaching an MCP server inside the IDE is the cleanest of the four.

Codex CLI supports MCP fully. The ecosystem is OpenAI-aligned (Codex MCP servers for OpenAI tools, plus the open MCP catalog).

Gemini CLI supports MCP, with the extra hook of Google Search grounding as a built-in tool (no MCP server needed to query live docs), plus an extensions system and a documented hooks and policy-engine layer for gating what the agent is allowed to do. Remember the context-file difference: it reads GEMINI.md by default, and you need context.fileName in settings.json before it will pick up a shared AGENTS.md.

Frequently asked questions

Can I use Cursor and Claude Code together?

Yes, and most production teams do. Cursor handles inline edits and tab completion; Claude Code handles autonomous multi-file dispatches. Cursor ships a Claude Code extension that surfaces sessions inside the editor. The two share git worktrees cleanly because Claude Code isolates per-session anyway.

Is Gemini CLI dead?

No. An earlier version of this page reported that Google would retire Gemini CLI on 18 June 2026 in favour of Antigravity CLI. That shutdown did not happen. As of 5 October 2026 the repository has 107,000+ stars, a stable v0.62.0 release from 29 September 2026, nightly builds landing daily, an Apache 2.0 licence, and no deprecation or migration notice in the README or releases page. The free tier is unchanged at 60 requests/minute and 1,000 requests/day on a personal Google account.

Which agent has the highest SWE-bench score?

As measured in May 2026: GPT-5.5 in Codex CLI at 88.7% on SWE-bench Verified, against Claude Opus 4.7 at 87.6% in Claude Code, with Codex ahead on Terminal-Bench 2.0 at 82.0% versus 69.4%. Treat all four of those numbers as historical. Both models have been superseded — Artificial Analysis's Intelligence Index v4.3.2 now scores Claude Opus 5.5 (Max) at 57.62 and GPT-6 Astra (Max) at 52.67 against Opus 4.7 (Max)'s 40.69 and GPT-5.5 (Xhigh)'s 38.36 — and Terminal-Bench 2.x itself has been moved to Artificial Analysis's legacy evaluations, replaced by Terminal-Bench 4.0. A 1.1-point gap on a superseded benchmark between two superseded models should not decide your tooling.

Which one is cheapest for a working engineer?

At $20/mo, Codex Plus typically delivers more per-task because of ~3-4x lower token consumption per workflow. Cursor Pro at $20/mo gives you unlimited tab completions plus a $20 credit pool. Claude Code Pro at $20/mo includes Opus 4.7 access but token quotas reset on a tight 5-hour window. Gemini CLI is the genuine zero-cost option — 1,000 requests a day on a personal Google account, with no deadline attached.

Do these agents replace human developers?

No. They make senior developers materially faster on multi-file work, but every agent we tested still produces diffs that need review for architectural fit, security, and edge cases. The teams winning with agents in 2026 are pairing them with engineers who have strong system-design skills. If you're hiring, this is where Codersera's vetting matters — we screen for the architectural judgment that agents can't replace.

Should I learn one or all four?

Learn one IDE-resident agent (Cursor) and one terminal-resident agent (Claude Code or Codex). Those two cover ~95% of real workflows. Gemini CLI is worth knowing if you're in the Google ecosystem, want an auditable open-source agent, or want a free option for personal projects — its free tier has no end date.

The bottom line

The 2026 AI coding agent market has consolidated to four serious surfaces. Cursor Composer owns the IDE. Claude Code, Codex CLI and Gemini CLI fight over the terminal, and all three are still fighting — the Gemini CLI sunset that was widely reported for June 2026, including on this page, never arrived. The winners are picked by workflow, not by leaderboard position, and that is more true now than it was in May: every model named on this page has been superseded at least once, while the tooling differences have barely moved. Pick for the surface and the ecosystem, then swap models underneath as they ship.

If you're building a remote engineering team and trying to figure out which agents to standardize on, that's the work of an architect, not a procurement decision. Codersera helps companies hire vetted remote developers who already work fluently with these agents — Cursor power users, Claude Code dispatchers, Codex CI engineers — so you skip the ramp-up.