Antigravity 2.0
Summary
Most AI coding assistants stop at suggestion — you still run the test, read the error, iterate manually, and wonder why you added a tool at all. Project IDX with Google's AI agents closes that loop by running code, checking output in a browser, and revising until the result passes.
The vendor describes Project IDX as a browser-based IDE where agents handle multi-step coding tasks end-to-end: writing code, executing it, observing what breaks in a live preview, and self-correcting before handing back control. Multi-model support means you are not locked to a single provider when one model handles your stack better than another. The free tier exists but carries usage caps that surface quickly on longer agentic runs — teams hitting those caps mid-task face a hard stop, not a graceful queue. Browser-based architecture removes local setup friction but also removes offline access and the deep editor customization that engineers who have spent years tuning their environment tend to miss.
Bottom line: Pick this when you need an agent that can write, run, verify, and revise code in a single automated loop — plan a workaround when your team's workflow depends on the deeply customized local IDE or persistent session state that a browser-hosted environment cannot replicate.
Pricing Plans
Usage-BasedLast verified 2 days ago- Price
- $0-$200/month
- Free Tier
- Basic weekly rate limits
Individual
Experience Antigravity without a subscription plan
- Access to Gemini 3.5 Flash, Gemini 3.1 Pro, Gemini 3 Flash, Claude Sonnet & Opus 4.6, gpt-oss-120b
- Unlimited Tab completions
- Unlimited Command requests
- Basic weekly rate limits
Google AI Pro
See how it is like to build, work, and automate with agents
- Everything in Individual
- More generous rate limits
- Flexible AI credit pool
Google AI Ultra
Leverage Antigravity as your daily driver with higher access to our latest Gemini models
- Everything in Pro
- More generous rate limits
- Flexible AI credit pool
View full pricing on antigravity.google →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Self-verifying execution loop — the agent runs code, observes live browser output, and revises without waiting for you to relay what broke, which means you stop being the error-relay between your AI tool and your test environment.
- Multi-model support in a single environment, so switching the underlying model when one handles your framework better is a configuration change rather than a tool migration.
- Browser-based access with no local setup, which means onboarding a new developer or spinning up a fresh environment takes minutes rather than an afternoon of dependency resolution.
- Multi-agent task splitting lets separate agents handle discrete parts of a complex task in parallel, cutting the wall-clock time on multi-step workflows that a single-agent loop would process serially.
- API access means the agentic core can be called from external pipelines, so teams integrating AI into CI or build systems are not forced to use only the browser interface.
Cons
Sign in to edit- Free tier usage caps terminate agentic runs mid-task when a multi-step job exceeds the allotment — there is no graceful queue, the session stops, and teams restart manually or upgrade to a paid tier before they have fully evaluated whether the tool fits.
- No self-hosted option and no offline access: teams with data residency requirements, air-gapped environments, or security policies restricting cloud-only tooling cannot use this at all, and those teams move to locally-deployable alternatives rather than filing exception requests.
- Browser-based execution means editor customization stops at what Google exposes in the interface — developers who depend on a specific plugin, language server configuration, or terminal workflow find the ceiling fast, and the path forward is maintaining a second local environment for the tasks IDX cannot handle.
- Complex conditional branching across more than a few agents strains the multi-agent coordination layer; community reports describe tasks with deep dependency chains producing inconsistent results, and teams handling those workflows add manual checkpoints that undercut the automation they bought the tool to achieve.
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About
- Platforms
- macOS, Windows, Linux, Web-based
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- 2026-06-01T05:57:18.631Z
Best For
Who it's for
- Developers building with AI agents
- Teams automating complex coding tasks
- Developers seeking multi-model support in one IDE
- Projects requiring browser-based verification
- Developers migrating from traditional IDEs to agent-driven development
What it does well
- Multi-agent code generation and execution
- Automated UI testing and browser interaction
- Complex multi-step development tasks
- Self-verifying code workflows
- Developer IDE replacement for agentic workflows
Integrations
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Frequently Asked Questions
- Is Antigravity 2.0 free?
- Antigravity 2.0 is a paid tool ($0-$200/month). No permanent free tier is offered.
- Is Antigravity 2.0 open source?
- No — Antigravity 2.0 is a closed-source tool. Source code is not publicly available.
- Does Antigravity 2.0 have an API?
- Yes. Antigravity 2.0 exposes a developer API. See the official documentation at https://antigravity.google for details.
- When was Antigravity 2.0 released?
- Antigravity 2.0 was first released in 2025.
- What platforms does Antigravity 2.0 support?
- Antigravity 2.0 is available on: macOS, Windows, Linux, Web-based.
Hours Saved & ROI Stories Community
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Curated lists that include this category
Project IDX is Google’s browser-based developer environment built for agentic coding workflows. The core loop the vendor describes: an agent takes a task, writes code, spins up a live preview, interacts with the running application through browser control, reads what fails, and iterates — without you running each step manually. Multi-agent coordination means separate agents can handle discrete parts of a task in parallel, with results fed into a shared context rather than bottlenecked through a single model call.
The differentiating feature the vendor surfaces is self-verifying code execution. Where most AI code tools generate a suggestion and stop, IDX agents observe actual runtime behavior — clicking through a UI, reading what renders, catching errors that only appear when the code runs — and use that feedback to revise. This closes the gap between ‘the code looks right’ and ‘the code works,’ which is where most AI-assisted development still requires a human in the middle.
The environment fits teams who want to automate complex, multi-step development tasks without maintaining local infrastructure. It is a poor fit when your workflow requires persistent local state, offline capability, or the kind of editor-level customization that years of dotfiles and plugins produce. The vendor confirms there is no self-hosted option, so all compute and context live in Google’s infrastructure — a constraint that matters to teams with data residency requirements or security policies that prohibit cloud-only tooling.
API access is confirmed, which means the agentic capabilities can be integrated into external pipelines rather than used exclusively through the browser interface. The Organization plan gates team-level features, and the free tier’s usage caps make it viable for evaluation and light use but not for sustained multi-agent runs on production-scale tasks.
