May 20, 2026 · 9 min read

Antigravity 2.0 vs Claude Code vs Codex CLI: AI Coding Agents Compared (May 2026)

The AI coding agent landscape shifted dramatically at Google I/O 2026. With the launch of Antigravity 2.0 powered by Gemini 3.5 Flash, developers now have three serious contenders for their terminal-based AI assistant: Google’s Antigravity, Anthropic’s Claude Code, and OpenAI’s Codex CLI.

This updated comparison breaks down every meaningful difference between these tools — speed, code quality, context windows, sandboxing, pricing, and real-world benchmarks — so you can pick the right agent for your workflow.

If you’re coming from our earlier Claude Code vs Codex CLI vs Gemini CLI comparison, this article reflects the major changes introduced with Antigravity 2.0 and the latest model updates across all three platforms.

Quick Comparison Table

Feature	Antigravity 2.0	Claude Code	Codex CLI
Maker	Google	Anthropic	OpenAI
Model	Gemini 3.5 Flash	Claude Sonnet/Opus	GPT-5.4/Mini
Speed	289 tok/s	67 tok/s	71 tok/s
Components	Desktop + CLI + SDK	CLI only	CLI only
Context window	1M tokens	200K tokens	200K tokens
Sandbox	Yes (Linux sandbox)	No (runs locally)	Yes (Docker/Cloudflare)
Custom agents	SDK + Markdown	Natural language	Agents SDK (code)
MCP support	Yes	Yes	Yes
Cloud automation	Via SDK	Routines	Via Agents SDK
Pricing	$20/mo (Pro)	$20/mo (Pro) or API	$20/mo (Plus) or API
Open source	CLI is open source	No	No
YOLO mode	`--yolo`	`--dangerously-skip-permissions`	`--dangerously-bypass-approvals`

What Changed: The Antigravity 2.0 Launch

Google I/O 2026 didn’t just iterate on Gemini CLI — it replaced the entire product category. Antigravity 2.0 is a full platform that bundles a desktop application, a CLI tool, and an SDK for building custom agents.

The key changes that matter for this comparison:

Gemini 3.5 Flash now powers the agent, delivering 289 tokens per second — roughly 4x faster than both Claude Code and Codex CLI. Read our complete Gemini 3.5 Flash guide for the full breakdown.
1 million token context window means you can load entire codebases without chunking or summarization.
Linux sandbox provides isolated execution without requiring Docker setup.
SDK for custom agents lets you build production automation pipelines, not just interactive coding sessions.
Open source CLI — Google open-sourced the CLI component, making it the only open-source option among the three.

For developers already using Gemini CLI, check our migration guide for using Gemini 3.5 Flash with Antigravity CLI.

Feature Comparison

Components and Architecture

Antigravity 2.0 stands alone as a multi-component platform. The desktop app provides a visual interface for agent management, the CLI handles terminal workflows, and the SDK enables programmatic agent creation. This three-layer approach means you can prototype in the desktop app, iterate in the CLI, and deploy via the SDK.

Claude Code remains a focused CLI tool. Its strength is simplicity — install it, point it at your codebase, and start coding. No desktop app, no SDK, just a powerful terminal agent. For teams that want to automate workflows, Claude Code Routines provide a natural-language approach to defining repeatable tasks.

Codex CLI is also CLI-only but compensates with the strongest sandboxing story. Its Docker and Cloudflare Workers integration means your agent runs in complete isolation. The OpenAI Agents SDK extends Codex into a programmable automation layer, though it requires writing code rather than markdown definitions.

Context Windows

The 1M token context window in Antigravity 2.0 is a genuine differentiator. At 200K tokens, both Claude Code and Codex CLI require strategies for large codebases — selective file loading, summarization, or multi-turn conversations that build context incrementally.

With 1M tokens, Antigravity can ingest an entire medium-sized project (think: a full Next.js application with 200+ files) in a single context. This reduces hallucination from missing context and eliminates the need for manual file selection.

Sandbox and Security

Codex CLI has the most robust sandbox implementation. Docker containers provide full OS-level isolation, and Cloudflare Workers enable cloud-based execution without local resource consumption. Read our Codex CLI complete guide for setup details.

Antigravity 2.0 introduces a Linux sandbox that runs locally. It’s simpler to set up than Docker but provides less isolation than a full container.

Claude Code runs directly in your local environment with no sandbox. It relies on permission prompts to prevent destructive actions. The --dangerously-skip-permissions flag bypasses these, which is useful for automation but requires trust in the agent’s judgment.

Custom Agents and Automation

All three tools support MCP (Model Context Protocol), which means they can connect to external tools, databases, and APIs through a standardized interface.

Where they differ is in how you build custom agents:

Antigravity: Markdown-based agent definitions via the SDK. Low barrier to entry, declarative approach.
Claude Code: Natural language routines. Describe what you want in plain English, and the agent follows the instructions.
Codex: Python-based Agents SDK. Most flexible but requires programming knowledge.

For a deeper dive into the agent-building capabilities, see our comparison of coding agents in 2026.

Model Benchmarks

The underlying models determine code quality, reasoning ability, and tool use. Here’s how they compare on the latest benchmarks:

Benchmark	Gemini 3.5 Flash	Claude Opus 4.7	GPT-5.5
Terminal-bench	76.2%	66.1%	78.2%
SWE-Bench Pro	55.1%	64.3%	58.6%
MCP Atlas	83.6%	79.1%	75.3%

What the Benchmarks Tell Us

SWE-Bench Pro measures real-world software engineering tasks — fixing bugs, implementing features, and refactoring code across actual open-source repositories. Claude Opus 4.7 leads here at 64.3%, which translates to noticeably better code quality in complex refactoring and bug-fixing scenarios.

Terminal-bench evaluates how well models handle terminal-based workflows — file manipulation, build systems, debugging, and system administration. GPT-5.5 edges out at 78.2%, with Gemini 3.5 Flash close behind at 76.2%.

MCP Atlas tests tool use and multi-step reasoning with external integrations. Gemini 3.5 Flash dominates at 83.6%, reflecting Google’s investment in tool-use training for the Gemini family.

Speed Comparison

Speed isn’t just about convenience — it fundamentally changes how you interact with an AI coding agent.

Agent	Tokens/second	Time for 1000-token response
Antigravity 2.0	289 tok/s	~3.5 seconds
Codex CLI	71 tok/s	~14 seconds
Claude Code	67 tok/s	~15 seconds

At 289 tokens per second, Antigravity 2.0 is approximately 4x faster than both competitors. For iterative coding sessions where you’re making dozens of requests, this compounds into significant time savings. A 30-minute Claude Code session might take only 8-10 minutes with Antigravity at equivalent task complexity.

The speed advantage comes from Gemini 3.5 Flash’s architecture, which was specifically optimized for low-latency inference. Learn more in our Gemini 3.5 Flash complete guide.

Pricing

All three tools converge on the same price point for subscription access:

Plan	Antigravity 2.0	Claude Code	Codex CLI
Subscription	$20/mo (Google One AI Pro)	$20/mo (Anthropic Pro)	$20/mo (ChatGPT Plus)
API access	Pay-per-token	Pay-per-token	Pay-per-token
Free tier	Limited	Limited	Limited

The $20/month subscription is the sweet spot for individual developers. All three offer generous usage limits at this tier. For teams and heavy automation, API pricing varies significantly — Gemini 3.5 Flash is generally the cheapest per token due to its efficiency, while Claude Opus is the most expensive but delivers the highest code quality.

Best for Each Use Case

Speed and Agent Automation → Antigravity 2.0

If you value fast iteration, large context windows, and building custom agents, Antigravity 2.0 is the clear winner. The 4x speed advantage and 1M token context make it ideal for:

Rapid prototyping and iterative development
Large codebase navigation and refactoring
Building automated CI/CD agents via the SDK
Teams that want a unified platform (desktop + CLI + SDK)

Code Quality and Precision → Claude Code

If you’re working on complex codebases where correctness matters more than speed, Claude Code with Opus delivers the best results. Its SWE-Bench Pro lead of 64.3% translates to:

Fewer bugs in generated code
Better understanding of complex architectural patterns
Superior refactoring suggestions
More accurate bug diagnosis

See our Gemini CLI complete guide for how the previous generation compared, and our Claude Code Routines guide for maximizing Claude Code’s automation capabilities.

Sandboxing and Security → Codex CLI

If you need strict isolation — running untrusted code, testing destructive operations, or working in regulated environments — Codex CLI’s Docker + Cloudflare Workers sandbox is unmatched:

Full OS-level isolation via Docker
Cloud execution via Cloudflare Workers
No risk of accidental file system damage
Ideal for CI/CD pipelines and automated testing

Our Codex CLI complete guide covers sandbox configuration in detail.

Migration Paths

From Gemini CLI to Antigravity 2.0

The transition is straightforward since Antigravity 2.0 is the successor to Gemini CLI. Your existing Gemini CLI configurations and workflows carry over. The main change is access to the desktop app and SDK components.

From Claude Code to Antigravity 2.0

Your natural-language routines won’t transfer directly, but the markdown-based agent definitions in Antigravity’s SDK serve a similar purpose. MCP configurations are compatible across both tools.

From Codex CLI to Antigravity 2.0

The Agents SDK code won’t port directly to Antigravity’s markdown-based system, but the concepts map cleanly. You’ll lose Docker-based sandboxing but gain the Linux sandbox and 5x larger context window.

For a comprehensive guide on choosing between these tools, read our how to choose an AI coding agent in 2026 guide.

Frequently Asked Questions

Is Antigravity 2.0 better than Claude Code?

It depends on your priorities. Antigravity 2.0 is faster (289 vs 67 tok/s), has a larger context window (1M vs 200K tokens), and offers more components (desktop + CLI + SDK). However, Claude Code produces higher quality code on complex tasks, scoring 64.3% on SWE-Bench Pro compared to Antigravity’s 55.1%. Choose Antigravity for speed and platform breadth; choose Claude Code for code quality.

Can I use all three AI coding agents together?

Yes. Many developers use multiple agents for different tasks — Antigravity for rapid iteration and large-codebase exploration, Claude Code for complex refactoring, and Codex CLI for sandboxed testing. All three support MCP, making it easy to share tool configurations.

Which AI coding agent is fastest in 2026?

Antigravity 2.0 powered by Gemini 3.5 Flash is the fastest at 289 tokens per second. This is approximately 4x faster than both Claude Code (67 tok/s) and Codex CLI (71 tok/s). The speed difference is most noticeable in iterative coding sessions with many back-and-forth exchanges.

Are these AI coding agents safe to use on production code?

All three agents include permission systems that ask before making destructive changes. Antigravity uses a Linux sandbox, Codex CLI uses Docker containers, and Claude Code relies on permission prompts. For maximum safety, avoid YOLO modes (--yolo, --dangerously-skip-permissions, --dangerously-bypass-approvals) on production codebases.

Which AI coding agent has the best free tier?

All three offer limited free access at the same $20/month subscription price point. Google’s free tier for Antigravity includes access to Gemini 3.5 Flash with rate limits. Anthropic and OpenAI offer similar limited free tiers. For serious development work, the $20/month subscription on any platform removes most restrictions.

Do these AI coding agents support MCP (Model Context Protocol)?

Yes, all three — Antigravity 2.0, Claude Code, and Codex CLI — support MCP. This means you can connect them to databases, APIs, and external tools through a standardized protocol. Antigravity scores highest on the MCP Atlas benchmark (83.6%), suggesting the best tool-use capabilities. See our MCP complete developer guide for setup instructions.