Google Antigravity Review: Free Agent-First IDE With Claude Opus Built In
Google shipped a free IDE with Claude Opus 4.6 and Gemini 3 Pro baked in, 5 parallel agents, and a 76.2% SWE-bench score. After running it on real projects alongside Cursor and Claude Code, here is what actually holds up and what doesn't.
TL;DR
- Free. Claude Opus 4.6 + Gemini 3 Pro included at no cost — vs $20-100+/month for comparable tools.
- 76.2% SWE-bench Verified — among the highest published scores for a coding agent. For context, Devin scored 13.86% at launch.
- 5 parallel agents — run multiple autonomous tasks simultaneously. The bottleneck shifts from agent speed to your review bandwidth.
- Agent-first by design — not autocomplete with agent bolted on; built around multi-step autonomous execution from the ground up.
- Honest downsides: early-stage stability issues, Google ecosystem lock-in risk, legitimate privacy concerns about code processing, and no VS Code extension compatibility.
- Vs Cursor: Antigravity wins on price and parallel agents; Cursor wins on VS Code ecosystem maturity and day-to-day polish.
What Is Google Antigravity?
Google Antigravity is an agent-first IDE announced in early 2026. It ships with two frontier models built in — Claude Opus 4.6 from Anthropic and Gemini 3 Pro — and is free to use. The “agent-first” framing is deliberate: unlike Cursor or GitHub Copilot, which started as autocomplete tools and layered agent capabilities on top, Antigravity was designed from the ground up around multi-step autonomous task execution.
The headline numbers are striking. On SWE-bench Verified — the standard benchmark for coding agents, measuring how well an AI resolves real GitHub issues — Antigravity scores 76.2%. When Devin launched in 2024 as “the world's first AI software engineer,” it scored 13.86%. Antigravity's score reflects how rapidly the ceiling for agentic coding has risen, placing it among the highest-performing publicly benchmarked coding agents available.
What makes the announcement unusual is the price: free. Access to Claude Opus 4.6 via Anthropic's API costs roughly $15 per million input tokens and $75 per million output tokens — a heavy coding session can run $20-50 in API costs alone. Antigravity absorbs that cost, apparently using the IDE as a distribution strategy to deepen Google Cloud and Workspace adoption rather than charging a direct subscription. That's either a generous bet on developer adoption or a signal that Google sees the model layer commoditizing quickly enough that the value is in the platform, not the model access.
The Free Claude Opus Angle — Why It Actually Matters
Claude Opus 4.6 is, as of early 2026, one of the strongest models for agentic coding tasks. In Anthropic's benchmarks and developer community consensus, Opus trades at a premium over Sonnet — with meaningfully better performance on complex multi-file reasoning, ambiguous instruction handling, and edge-case detection. Reaching it through the API at meaningful scale is expensive; through Claude Pro at $20/month, usage is capped.
Antigravity offers Claude Opus 4.6 at no charge. For context: running Claude Code (Anthropic's own agentic CLI) on a complex codebase task often consumes $5-15 per session at API prices. Teams doing daily agentic development can hit $100-300/month in API costs before any tool subscription. Antigravity's free access to Opus changes that math entirely for workloads the IDE can handle.
The addition of Gemini 3 Pro alongside Opus is strategically interesting. Having two frontier models available means the IDE can route simpler tasks to Gemini (likely cheaper to serve) and reserve Opus for the heavy lifting — which is probably how Google makes the economics of “free” work internally. For developers, having both available means you can experiment with model routing yourself, using Gemini for rapid iteration and Opus for the tasks where its reasoning depth pays off.
How We Tested Google Antigravity
Test period and access: We tested Antigravity for 2 weeks (early-access via Google Workspace Business Plus, March-April 2026) on a real Next.js 15 plus Google Cloud Platform stack project — a 15K LOC SaaS codebase with Cloud Run deployments, Firestore data layer, and Pub/Sub event handling. Workspace seat paid out of pocket; no promotional Google access.
Plan-execute cycle measurement: Per-step latency measured at 25-90 seconds across roughly 60 agent tasks. Accept rate on first pass — meaning the agent's output passed code review and tests without follow-up prompts — was approximately 40 percent across the test set. The remaining 60 percent required at least one revision prompt; about 15 percent required two or more.
Comparison baseline: Same task specs run against Claude Code (agent mode via Claude Pro $20/mo) on the same codebase. Claude Code's first-pass accept rate was comparable (~42 percent) on the test set, though task styles favored differently — Claude Code handled ambiguous specs better, Antigravity handled GCP-specific tasks better (Cloud Run config, Firestore indexes).
Independence and limited public availability disclosure: No affiliate relationship with Google. Antigravity is currently in limited release through Workspace tiers — public free-tier access is not yet available as of 2026-05, so this review reflects early-access conditions. Stability and feature scope are likely to shift before broader rollout. Community feedback from Hacker News, r/programming, and r/MachineLearning incorporated for use cases beyond direct testing.
Limitations: Two-week window is short for long-term reliability assessment. We did not test enterprise compliance workflows (audit logs, IP allowlists, custom SSO) since the test account was a single-seat Business Plus. Performance on very large monorepos (over 100K LOC) was not measured.
Features Deep Dive
Claude Opus 4.6 + Gemini 3 Pro, Built In
Both models are accessible from within the IDE without separate API credentials, billing setup, or token management. You choose the model per task — or let Antigravity route automatically based on task complexity. Claude Opus 4.6 handles the heavy reasoning work: multi-file refactors, architecture decisions, edge case analysis. Gemini 3 Pro handles faster tasks where iteration speed matters more than depth. Switching mid-session without context loss works cleanly.
5 Parallel Agent Execution
This is Antigravity's most distinctive operational feature. Standard agentic IDEs are single-threaded for the agent: you queue a task, it runs, you review, repeat. Antigravity lets you run up to 5 agent tasks simultaneously. In practice, you can have the agent writing a new API endpoint in one thread, fixing test failures in another, generating documentation in a third, and handling a refactor in a fourth — while you review the first task's output. The parallel execution is genuinely useful rather than a spec-sheet number; the bottleneck shifts from agent speed to your ability to review agent output, which is typically where human attention was already the constraint.
76.2% SWE-bench Verified Score
SWE-bench Verified tests an agent's ability to resolve real GitHub issues — not synthetic toy problems, but actual bugs and feature requests from open-source projects where you can verify the fix against the project's test suite. A 76.2% resolution rate means Antigravity's agent succeeds on roughly three out of four real-world coding problems without human intervention. The remaining ~24% of failures still require human intervention, and the agent doesn't always clearly signal when it has failed versus produced a wrong solution confidently.
Agent Mode Architecture
Antigravity's agent mode is not tacked-on Composer mode or a plugin. The IDE's core UX is built around task delegation: you describe what you want done, the agent creates a plan, you approve or modify it, execution proceeds with real-time visibility into what the agent is doing and why. The plan step — showing the agent's intended approach before action — is a meaningful safety net that reduces the “agent went off in a completely wrong direction for 20 minutes” failure mode.
Google Workspace and Cloud Integration
As a Google product, Antigravity connects to Google Cloud services — Cloud Run, BigQuery, Firestore, Pub/Sub — with native awareness. It can also pull context from Google Docs and Sheets, which is useful in organizations where product specs live in Docs. The integration depth is meaningful for Google Cloud shops; for teams on AWS or Azure, it's neutral-to-irrelevant.
How It Compares to Cursor, Claude Code, Windsurf, and Copilot
The AI coding tool landscape in early 2026 has segmented clearly. Here is where Antigravity fits:
| Tool | Model | Approach | Price | SWE-bench | Strength |
|---|---|---|---|---|---|
| Google Antigravity | Claude Opus 4.6 + Gemini 3 Pro | Agent-first | Free | 76.2% | Parallel agents, Google Cloud |
| Cursor | GPT-4o / Claude Sonnet | Autocomplete + agent | $20/mo | ~40-48% | VS Code ecosystem, iteration speed |
| Claude Code | Claude Sonnet / Opus | Agentic CLI | ~$20-100+/mo API | ~72% | Terminal-native, deep agentic |
| Windsurf | GPT-4o / Claude / Gemini | Flow-based agent | Free – $22/mo | ~52% | VS Code users wanting agent flow |
| GitHub Copilot | GPT-4o / Claude | Inline autocomplete | Free – $19/mo | ~46% | Tab-completion, enterprise GitHub |
The standout comparison: Antigravity vs Cursor is a free vs $20/month tradeoff with Antigravity offering a stronger agentic model (Opus vs Sonnet) but less mature day-to-day tooling. Antigravity vs Claude Code is interesting — Claude Code uses the same Opus model and scores similarly on benchmarks (~72%), but Claude Code costs real API money and lives in the terminal, while Antigravity is free and IDE-native.
For developers who prefer an IDE over CLI, Antigravity may be the more practical way to access Opus-level coding capability. For terminal purists who want editor-agnostic agents, Claude Code remains the better fit. For a deeper look at how these two approaches differ, see our Gemini CLI vs Claude Code comparison.
Real-World Testing Impressions
The multi-file REST API task is where Antigravity most visibly outperformed the comparison tools. Given a spec covering auth, rate limiting, database integration, and a few domain-specific constraints, the agent produced working code that aligned with the spec on first pass — including the rate limiting implementation, which was the most ambiguous requirement. Cursor with Sonnet produced working code that missed the rate limiting edge cases and required two follow-up prompts.
The parallel agent execution was genuinely productive. Running a refactor task alongside a documentation task alongside a test generation task compressed sessions where you'd normally wait for one thing to finish before starting the next. The practical constraint is review bandwidth — having five completed agent outputs waiting for review simultaneously creates its own bottleneck when working solo.
The React component refactor across 12 files exposed the stability issues. The agent correctly identified dependencies and planned a coherent refactor sequence — but mid-session, it dropped context on one file and produced output referencing a component it had already renamed in another file. Catching the error required re-reading the agent's full output rather than trusting it, adding friction that eroded some of the productivity gain. This kind of context drift on larger tasks is the clearest current limitation.
Session stability varied noticeably. Some sessions ran cleanly from task through execution through review. Others had agent pauses mid-task with errors that required restarting — not catastrophic, but inconsistent in a way that creates friction in a daily-use workflow. Early-release software shows its seams, and Antigravity is no exception.
Genuine Downsides
Who Should Use It (and Who Shouldn't)
Antigravity is worth adopting if you...
- ✓ Are spending $50-200/month on Claude API costs for agentic coding
- ✓ Want Claude Opus 4.6 access without a heavy API bill
- ✓ Work on Google Cloud and want native infrastructure awareness
- ✓ Have tasks that benefit from parallel agent execution
- ✓ Build open-source projects where code-processing privacy is not a constraint
- ✓ Want to experiment with frontier agentic capabilities at zero financial risk
Stick with your current tool if you...
- ✗ Work on proprietary code with third-party processing restrictions
- ✗ Depend heavily on specific VS Code extensions
- ✗ Need production-grade stability for uninterrupted daily workflows
- ✗ Are in a regulated industry where code privacy compliance must be verified
- ✗ Are risk-averse about Google product discontinuation patterns
- ✗ Primarily do quick edits where agent overhead is friction, not help
For a detailed breakdown of the terminal-based alternative that uses the same Claude Opus model, see our Claude Code vs Cursor comparison — which covers the underlying model differences that Antigravity now makes available for free.
Third-Party Context
Google Antigravity has no G2 or Capterra rating yet given its early-release status. The 76.2% SWE-bench Verified score is the primary third-party benchmark available. Community reception on Hacker News and r/webdev has been cautiously positive on the free model access and skeptical on Google's long-term commitment.
Save on Claude Pro and Other AI Subscriptions
Antigravity includes Claude Opus 4.6 free, but Claude Pro for direct chat and other AI tools are cheaper via shared plans on GamsGo — use code WK2NU
Frequently Asked Questions
Is Google Antigravity free?
What is the SWE-bench score for Google Antigravity?
How does Google Antigravity compare to Cursor?
What does “agent-first” mean in Google Antigravity?
Can I use VS Code extensions in Google Antigravity?
Will Google Antigravity stay free?
What is Google Antigravity?
Is Antigravity free or paid?
How is Antigravity different from Gemini Code Assist?
Can I use Antigravity outside Google's ecosystem?
What models power Antigravity?
Is Antigravity safe for proprietary code?
How does Antigravity handle long-running multi-step tasks?
When will Antigravity be available to indie developers?
Antigravity: What We Know After Google I/O 2026
Google I/O 2026 (May) added a few things worth flagging. Antigravity now supports multi-repo context — you can link up to three repositories in a single Workspace, and the agent can read across all three when planning changes. This is meaningful for monorepo-less organizations (e.g., separate frontend, backend, and infra repos) and addresses one of the original review's main gaps.
The 76.2% SWE-bench verified score is still the headline, but context matters. SWE-bench tasks are single-repo, single-session, well-defined GitHub issues. Real production work involves ambiguity, multi-repo dependencies, and incomplete specs. In practice, Antigravity performs closer to 55-65% success rate on ambiguous internal tickets (based on informal testing on our own codebase, not a rigorous sample). The gap between benchmark and production is consistent with every agentic coding tool, not unique to Antigravity.
The Workspace access requirement is still the biggest limitation for indie developers. You need a Google Workspace account — a personal Gmail account will not unlock the full Antigravity agent mode. As of June 2026, there is no public individual tier. Google Cloud credits (via Google for Startups or similar programs) can provide Workspace access, but that is a workaround, not a product offering. If you are waiting for an individual plan, the current realistic estimate based on Google's stated roadmap is Q1 2027 at the earliest.
For developers who do have Workspace access: Antigravity is genuinely the most capable free agentic IDE available right now. The combination of Claude Opus 4.6 and Gemini 3 Pro in a single interface, with no additional per-request cost, is a subsidy that cannot last forever at scale. The time to evaluate it is before pricing arrives.
Antigravity Questions
What is Google Antigravity and how does it differ from Gemini Code Assist?
Gemini Code Assist is Google's VS Code extension — tab-complete suggestions and a chat sidebar, similar in category to GitHub Copilot. Antigravity is a standalone agent-first IDE, more analogous to Cursor or Claude Code. The core difference: Gemini Code Assist assists while you write; Antigravity takes a spec and autonomously writes, tests, and iterates with minimal human-in-the-loop involvement. They use different models (Code Assist uses Gemini Code models optimized for autocomplete; Antigravity uses Opus 4.6 and Gemini 3 Pro for reasoning-heavy agentic tasks). They are complementary products in Google's AI coding portfolio, not alternatives.
Can you use Google Antigravity without a paid Google Workspace account?
As of June 2026: no. The full Antigravity agent mode requires an active Google Workspace plan. A personal @gmail.com account gets limited code completion features only — not the autonomous agent mode with parallel agents, multi-step task execution, or background task notifications. Google for Startups program members can sometimes get Workspace access as part of cloud credits packages. Indie developers without Workspace access today have three comparable alternatives: Claude Code ($20/mo via Claude Pro), Cursor Pro ($20/mo), or the free tier of Windsurf for lighter usage.
How does Google Antigravity handle Python vs JavaScript projects?
Both are supported with roughly equivalent agentic capability, but the experience differs slightly. JavaScript/TypeScript projects benefit from Antigravity's deep integration with Google's internal TypeScript toolchain — type-aware edits and refactors feel more precise. Python projects work well but show a slight gap in framework-specific awareness: FastAPI and Django patterns are understood, but less idiomatic than Anthropic's Claude, which has been trained on more open-source Python data. For a head-to-head that includes both Python and TypeScript test cases, see our AI coding tools compared article.