Google Antigravity is built for the “tell an agent what you want, then verify the result” era.
Instead of living in chat transcripts and tool logs, Antigravity centers the workflow on Artifacts: concrete deliverables like task lists, implementation plans, screenshots, walkthroughs, and browser recordings. The vibe is less “assistant whispering in your ear” and more “mission control with receipts”.
Pricing Tiers
Antigravity launched as a public preview that’s free for individuals, with quotas and rate limits that reset on a cadence. If you become a power user (or you need priority access), you will eventually care about whatever paid tiers Google ties to higher limits.
| Tier / Path | Price / Access | Key Features |
|---|---|---|
| Public Preview (Free) | $0 (individuals) | Full Antigravity experience, agent-first workflow, Artifacts-based verification, “generous” rate limits. |
| Paid Google AI tiers | Subscription (tier-dependent) | Higher quotas, priority access, smoother sustained sessions for heavy usage. |
| Enterprise | Custom | Team controls, compliance requirements, procurement-friendly support and governance. |
Tip: Treat Antigravity as a productivity multiplier. When it’s doing more work for you, it will naturally consume more quota. Plan for that.
Core Features & Capabilities
Verify with Artifacts, not logs
Antigravity turns agent work into reviewable outputs: plans, screenshots, walkthroughs, and recordings. You can comment directly on Artifacts and keep the agent moving.Two modes: Editor + Manager
Editor view feels familiar if you’ve used modern AI IDEs. Manager view is the “mission control” layer where you can orchestrate multiple agents across multiple workspaces.Agent access to the full loop
Agents can edit code, run commands in the terminal, and use a browser to reproduce bugs, validate UI, and confirm fixes.Model optionality
You are not locked into a single brain. Antigravity supports Google’s models and also third-party options, which is perfect when you want different strengths for different tasks.Learning and reuse
Antigravity treats learning as a primitive: agents can save useful context and snippets to improve future tasks and reduce repeated explaining.
Pros & Cons
Pros:
- Great for “do the whole task” workflows: reproduce issue → implement fix → validate → show proof.
- Artifacts make trust practical. You can review outcomes fast without spelunking logs.
- Manager view is a real advantage when you have parallel work streams.
- Plays nicely with multi-agent, multi-model setups.
Cons:
- It’s powerful enough to hurt you if you hand it sharp objects. Terminal access means you should build habits like scoped tasks, repo backups, and review checkpoints.
- There is still a learning curve to prompting agents well (clear acceptance criteria helps).
- Quotas exist, and serious usage can push you toward paid tiers.
Summary
| Category | Highlights |
|---|---|
| Ideal for | Builders who want agents to take on whole tasks, not just autocomplete |
| Best features | Artifacts-based verification, Manager view orchestration, editor/terminal/browser loop |
| Potential drawbacks | Requires install + account, quotas, needs guardrails for safe automation |
Further reading
| antigravity.google | Antigravity home | |
| developers.googleblog.com | Google Developers Blog announcement | |
| codelabs.developers.google.com | Getting started codelab | |
| theverge.com | Launch coverage and feature overview |
