Claude Code vs OpenAI Codex vs Google Antigravity: The Agentic Coding Tool Comparison

A BitsMinds analysis. In 2026 the interesting question is no longer “which model is best?” — we covered that in our model-by-model scorecard. The fight has moved up a layer, to the agents wrapped around those models: the tools that actually read your repo, run your tests, edit files and open pull requests. Three of them dominate the conversation — Anthropic’s Claude Code, OpenAI’s Codex and Google’s new Antigravity. They share a goal and almost nothing else.

How we compared them

These are products, not raw models, so a single benchmark would mislead. We weigh the things that actually decide which agent a team adopts: form factor (terminal, IDE or cloud), the model under the hood, orchestration (how many agents it runs and how you steer them), verification and trust (how you check what it did), extensibility (MCP, SDKs) and price. Where we cite coding numbers, they belong to each tool’s default model.

Two caveats up front. First, the benchmark figures come from different vendors under different conditions — Anthropic quotes Terminal-Bench 2.1 (74.6%) while OpenAI’s 82.0% is on Terminal-Bench 2.0 — so treat them as a map, not a verdict. Second, Antigravity is deliberately model-agnostic: it ships with Gemini 3 Pro but also runs Claude Sonnet 4.5 and open models, so its “score” is really a dial. This space moves weekly; validate against your own codebase.

Three tools, three philosophies

Claude Code is selling deep terminal autonomy. It lives in your shell as a command-line agent and is built to be handed a long, messy, multi-hour job. Its headline trick is Dynamic Workflows: Claude plans the work, spins up hundreds of parallel subagents (capped at 1,000, 16 concurrent) and verifies them before reporting back. Paired with Opus 4.8’s “most honest” self-review, the pitch is the agent you trust to drive the repo unattended.

OpenAI Codex is selling ubiquity. Codex is less a single app than one agent that shows up everywhere — a terminal CLI, an IDE extension, cloud delegation inside ChatGPT, a GitHub reviewer, even driving your Mac by reading the screen — all sharing one account and context. With roughly 4 million weekly active developers and a separate agent that reviews your code before you commit, its edge is reach: the capable default already wired into the tools your team uses.

Google Antigravity is selling agent-first control. Rather than bolt an agent onto an editor, Antigravity rebuilds the IDE around a Manager — a mission-control surface where you spawn, orchestrate and watch multiple agents work asynchronously across editor, terminal and browser. Agents report through Artifacts (plans, screenshots, browser recordings) you can comment on like a Google Doc. It is model-agnostic and free for individuals.

The model under the hood

On raw coding ability, the two single-vendor agents are neck and neck: GPT-5.5 behind Codex posts 88.7% on SWE-bench Verified, Opus 4.8 behind Claude Code 88.6% — a rounding error apart. Codex’s GPT-5.5 also leads Terminal-Bench (82.0% on v2.0 versus Claude’s 74.6% on the harder v2.1), though the version gap makes that comparison softer than it looks.

Antigravity’s default Gemini 3 Pro trails on SWE-bench Verified (80.6%), but that number is the least meaningful of the three: because Antigravity lets you pick the model, a team that cares about the benchmark can simply run Claude Sonnet 4.5 inside it. The model is a setting, not a destiny — which is exactly Google’s argument.

Form factor: where each one lives

This is the real dividing line. Claude Code is terminal-first — a CLI agent with thin IDE extensions, happiest when it owns your shell and your test runner. Codex is everywhere — the same agent in the terminal, your editor, the cloud and GitHub, so work started on your laptop can finish on a server while you review the diff on your phone. Antigravity is a full IDE — a desktop application (a heavily modified VS Code fork) whose center of gravity is the Manager, not a file you are editing.

The practical translation: pick Claude Code if you already live in the terminal and want the agent to disappear into it; pick Codex if you want one consistent agent across every surface your team already touches; pick Antigravity if you would rather supervise a fleet of agents from a dedicated cockpit than babysit one in a chat box.

Orchestration & verification

All three can run more than one agent, but they frame it differently. Claude Code’s Dynamic Workflows are model-driven: Claude decides when to fan out into subagents and stitches the results back together itself. Codex leans on cloud parallelism, delegating tasks to run server-side while you keep working. Antigravity makes orchestration the main UI — the Manager is built for a human to launch and monitor several agents at once.

Verification splits the same way. Claude Code’s answer is honesty: Opus 4.8 is tuned to flag its own failed steps rather than paper over them. Codex’s answer is a second pair of eyes: a separate review agent checks the work before you commit. Antigravity’s answer is evidence: Artifacts give you a plan, screenshots and a browser recording so you can audit the outcome without reading raw logs. For unattended work that touches money, code or compliance, that “how do I trust it?” question often matters more than a benchmark point.

Price & access

Access is where Antigravity presses hardest. It is free for individuals, with paid Google AI Pro and a $100/month AI Ultra tier (5× higher Antigravity limits) for heavy users. Claude Code and Codex both come bundled with their labs’ $20/month consumer plans — Claude Pro and ChatGPT Plus — and scale up through Claude Max ($100+) and ChatGPT Pro ($200), or metered API rates ($5 in / $25 out per million tokens for Opus 4.8) for automation.

The free entry point matters for adoption: it lets Google put an agent-first IDE on every student’s and hobbyist’s machine at zero cost, the same playbook that built earlier developer ecosystems. Codex counters with sheer installed base — about 4 million weekly developers already inside ChatGPT — and Claude Code counters with depth that power users are willing to pay for.

The full scorecard

Highlighted cell = leader on that row. Benchmark figures are for each tool’s default model and are lab-reported or drawn from public leaderboards (llm-stats, Vellum, Artificial Analysis) as of late May 2026; benchmark versions and run conditions differ between vendors. Antigravity is model-agnostic, so its numbers move with whichever model you select.

Read across the rows and the pattern is clear: Codex wins on raw model scores and reach, Antigravity wins on flexibility and price, and Claude Code wins on the harder-to-tabulate axis of trustworthy, deep autonomy. No single column sweeps — which is the whole point.

The verdict: which one should you use?

Pick Claude Code when the work is deep, autonomous engineering you want to hand off and audit — large refactors, repo-scale migrations, multi-hour agent runs in the terminal. Its parallel subagents and honesty posture make it the safest pick when you cannot watch every step.

Pick OpenAI Codex when you want one capable agent everywhere, with the least friction. If your team already lives in ChatGPT, VS Code and GitHub, Codex is the default that meets them there — in the cloud, on the desktop, even on the phone — and rarely the wrong answer.

Pick Google Antigravity when you want to run a fleet of agents from mission control, stay free of single-model lock-in, or simply start for nothing. Its Manager-and-Artifacts design is the most opinionated bet that the future of coding is supervising agents, not chatting with one.

The deeper point mirrors the model layer: the “best agent” question is the wrong one. The tools have split by philosophy — terminal depth, ubiquity, agent-first control — and the right move for many teams is to keep more than one on hand and reach for the one that fits the job.