Choose Google Antigravity if you want agents orchestrating work across an editor, terminal and browser, including asynchronous tasks and structured artifacts. Choose Cursor if you want a focused AI coding editor with selectable modes, checkpoints, broad integrations and clearly published team pricing. Both offer a free way to start. Your decision should follow the work you actually delegate, the models and usage limits you need, and whether remote execution is acceptable for your code.
Google Antigravity vs Cursor at a glance
These products overlap, but they are built around different centers of gravity. Antigravity treats the agent as the primary control surface and brings the editor, terminal and browser into one environment. Cursor starts with an editor and adds an increasingly capable coding agent, read-only exploration, custom tool combinations and optional remote execution.
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| Decision axis | Google Antigravity | Cursor |
|---|---|---|
| Primary interaction | Agent-first environment spanning editor, terminal and browser (Google Antigravity documentation). | Editor-centered Agent with code search, edits, terminal commands and checkpoints (Cursor Agent documentation). |
| Parallel or background work | Asynchronous local agents and browser-use agents. | Cloud or Background Agents running in isolated remote virtual machines. |
| Reviewable deliverables | Plans, diffs, diagrams and browser recordings called artifacts. | Checkpoints, diffs and pull-request handoff for cloud work. |
| Product surfaces | Desktop application, agy command-line interface, IDE extensions and a Python SDK. |
Desktop editor plus browser and mobile agent surfaces and integrations. |
| Free entry point | Individual plan at $0 per month, with multiple agent models, unlimited Tab completions and unlimited Command requests subject to basic weekly rate limits (Google’s 2026 pricing page). | Hobby plan at no charge, with limited agent requests and tab completions (Cursor’s 2026 pricing page). |
| Published paid prices | Pro and Ultra add higher rate limits and flexible AI credit pools; prices were not stated in the supplied 2026 snapshot. | Pro: $20 per month; Ultra: $200 per month; Teams: $40 per user per month; Enterprise: custom pricing. |
| Best fit | Developers who want multi-surface orchestration and Google ecosystem integration. | Developers who want a concentrated AI editor with mature agent controls and integrations. |
The table is a starting point, not a benchmark. Neither vendor’s published plan name tells you exactly how many long-running tasks your repository will support. Rate-limit behavior, model entitlements, indexing, remote-agent charges and administrative requirements can change the practical cost.
What Google Antigravity is
An agent-first development environment
Google describes Antigravity IDE as “an agentic development environment built for the agent-first era.” In practical terms, the agent is not limited to suggesting a line while you remain in the editor. It can coordinate work through the coding surface, a terminal and a browser, allowing a task to move between code changes, command execution and browser interaction.
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This design suits work that crosses boundaries. A request might involve inspecting a repository, changing several files, running a command, checking a web interface and returning evidence of what happened. The value is the shared control surface: you can ask for the work as a goal instead of manually switching among unrelated tools for every subtask.
Synchronous and asynchronous operation
Antigravity documents synchronous pair programming as well as asynchronous background workflows. Synchronous use keeps you in the loop while an agent proposes or performs the next action. Asynchronous local agents let a longer task continue while you work on something else, with the result available for review later. Browser-use agents extend that asynchronous model to browser-oriented tasks.
“Asynchronous” does not mean “unattended and automatically safe.” You still need to define the repository scope, credentials, allowed network access and review points. Treat an agent that can use a browser or terminal as an operator with capabilities, not as an autocomplete box.
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Artifacts instead of an unstructured chat log
Antigravity documents artifacts such as plans, diffs, diagrams and recordings. These outputs give a reviewer something more concrete than a long conversation. A plan can expose the intended sequence before edits begin; a diff shows the exact code change; a diagram can communicate relationships; and a browser recording can show what an agent did in a web context.
Artifacts are especially useful when several people need to inspect progress asynchronously. They also create a natural checkpoint for deciding whether to continue, revise the plan or stop before a risky command.
Multiple ways to connect
The product family includes a desktop app, the agy CLI, IDE extensions and a Python SDK. That breadth matters if your workflow is not confined to one editor window. A command-line or SDK entry point can fit automation and internal tooling, while the desktop app can provide the visual control surface. The available data does not establish that every feature is available identically across all surfaces, so verify feature parity before standardizing on one interface.
What Cursor is
An editor-centered coding agent
Cursor’s official Agent documentation says, “Agent is Cursor’s assistant that can complete complex coding tasks independently, run terminal commands, and edit code.” The editor remains the place where you inspect context, review changes and decide what to accept. Agent can work across multiple files rather than limiting itself to the current line or buffer.
That focus is useful when most of your day is conventional software development: navigate a codebase, ask for an implementation, run tests, inspect a diff and iterate. Cursor’s design keeps those activities close together instead of making the browser or a separate orchestration layer the center of the experience.
Rank #2
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Modes for different levels of autonomy
Cursor documents three relevant modes. Agent is for autonomous, multi-file work. Ask is read-only exploration, useful when you want explanations, code search or an impact assessment without permitting edits. Custom modes let you select specialized combinations of tools for a repeatable workflow.
The distinction is operationally important. Starting in Ask mode can reduce accidental changes while you learn an unfamiliar repository. Moving to Agent mode makes sense after you have a plan and know which files should change. A Custom mode can encode a team convention, such as allowing repository search and tests while excluding a deployment command.
Checkpoints and Projects
Agent can create checkpoints, giving you a recovery point while a complex task evolves. Checkpoints are not a substitute for version control; commit meaningful states to your normal repository and use checkpoints as an additional short-term safety net.
Cursor also offers Projects for larger work in which a coordinator delegates to other agents. This is aimed at decomposition: one piece of work can be assigned to an agent while another piece proceeds separately. The quality of the result still depends on clear task boundaries, shared repository context and a human review of the combined changes.
Cloud and Background Agents
Longer tasks can move to Cloud or Background Agents running in isolated remote virtual machines. Those environments can install dependencies, run tests and open pull requests. Because the work continues without your laptop remaining open, remote agents are useful for slow builds, broad refactors and queued maintenance tasks.
The trade-off is a different security model. A remote machine must receive enough repository context and credentials to do its job, and an agent that can run commands may encounter untrusted instructions in a dependency, issue or file. Use repository scoping, network restrictions, secret management and human review before enabling this mode on sensitive projects.
How the daily workflows differ
Starting a task
With Antigravity, frame the request as an outcome that may involve code, a command and a browser check. Ask for a plan artifact first when the task is broad. Review the proposed files, external actions and expected evidence before allowing execution.
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With Cursor, begin by choosing the least-permissive mode that can answer your question. Use Ask for reconnaissance, then switch to Agent for an approved implementation. If the task will outlive your local session, decide whether a Cloud or Background Agent is appropriate and what it may access.
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Handling multi-file changes
Both products can work beyond a single file, but their review objects differ. In Antigravity, a plan and diff artifact can form the review package, with a diagram or recording when the task crosses an interface. In Cursor, the editor, checkpoint and diff are the core loop. The practical choice is whether your team prefers a broader activity record or an editor-native review cycle.
Running commands and tests
Keep commands narrow and observable. Ask the agent to state what it will run, why it needs the command and what result would count as success. Cursor’s foreground agents normally request approval before terminal commands. Background agents run commands in remote infrastructure, so approval happens through your task design and repository policy rather than a prompt at every step.
Antigravity’s terminal integration enables the same class of work, but the available documentation in this comparison does not define an identical approval policy for every surface. Establish your own rule: no destructive command, deployment or credential access without an explicit human decision.
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Working with browser tasks
Antigravity’s browser-use agents are a differentiator when a task needs web interaction as part of the development loop. A browser recording can make the result easier to audit. Cursor’s documented emphasis is the coding editor and its remote agents; do not assume that a browser workflow has the same controls or evidence format across the two products.
Reviewing and handing off work
For a local handoff, require a clean diff, test output and a short statement of unresolved issues. Antigravity’s artifacts can package that context. Cursor’s checkpoints and, for cloud work, pull-request handoff can fit teams that already review changes through pull requests. In either product, the human reviewer remains responsible for licensing, security, correctness and compatibility with project conventions.
Pricing, limits and the real cost of use
The following figures are the published 2026 snapshot and are subject to change. A subscription price is not a usage guarantee; compare what happens when you reach a rate limit and which models are included.
| Plan | Published price | What is stated | What to verify |
|---|---|---|---|
| Antigravity Individual | $0/month | Multiple agent models, unlimited Tab completions and unlimited Command requests, subject to basic weekly rate limits. | Exact weekly allowance, model-specific limits and reset behavior. |
| Antigravity Pro | Not stated in the 2026 snapshot | Higher rate limits and flexible AI credit pools. | Price, credit depletion, rollover and model entitlements. |
| Antigravity Ultra | Not stated in the 2026 snapshot | Higher rate limits and flexible AI credit pools. | Price, credit depletion, rollover and enterprise suitability. |
| Cursor Hobby | Free | Limited agent requests and tab completions. | Current request allowance and model access. |
| Cursor Pro | $20/month | Paid individual tier listed on Cursor’s 2026 pricing page. | Included usage, overage behavior and model-specific limits. |
| Cursor Ultra | $200/month | Higher-priced individual tier listed on Cursor’s 2026 pricing page. | Whether your workload actually uses the additional allowance. |
| Cursor Teams | $40/user/month | Team tier listed on Cursor’s 2026 pricing page. | Administrative controls, billing terms and included usage. |
| Cursor Enterprise | Custom pricing | Enterprise tier is available with a negotiated price. | Data handling, support, identity, retention and contract terms. |
How to compare a free tier fairly
Run the same representative tasks in both free plans instead of counting autocomplete suggestions. Record how many agent requests you can complete, which models are available, how quickly limits appear, whether a reset is weekly or otherwise, and how much manual cleanup remains. A tool that finishes fewer but larger tasks may be more useful than one that produces many small suggestions.
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Usage can move between dimensions: a model may consume credits, a background task may incur a separate charge, and a team may need administrative controls even when individual seats are inexpensive. Ask four questions before buying: What is included? What is rate-limited? What happens at the limit? Which features require a higher tier or remote execution?
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Privacy and security differences
Cursor indexing and Privacy Mode
Cursor says Privacy Mode prevents code from being used for training. Its codebase indexing sends chunks to Cursor to compute embeddings; after that process, plaintext code ceases to exist, while embeddings and metadata remain. This distinction matters for repositories containing proprietary algorithms, customer data or regulated information: removing plaintext from one processing stage does not mean that all derived data disappears.
Document your indexing decision. Identify which repositories are indexed, who can query the resulting context, how long embeddings and metadata remain under the current terms, and whether model providers receive prompts or retrieved snippets. The published statement in this comparison does not answer every retention question, so obtain the current contractual wording for sensitive workloads.
Foreground approval versus remote autonomy
Cursor’s foreground agents normally ask for approval before terminal commands. Background agents automatically run commands in remote infrastructure. Cursor warns that this increases exposure to prompt-injection and data-exfiltration risks. A malicious instruction in a repository file, issue or dependency can attempt to redirect the agent, reveal secrets or send data elsewhere.
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- Use short-lived credentials with no production privileges.
- Block unnecessary network destinations and outbound uploads.
- Keep secrets out of files that an agent can read; inject only narrowly scoped values when unavoidable.
- Require a human to inspect diffs, test logs and pull requests before merging.
Antigravity enterprise controls
Antigravity’s overview documents enterprise security, regional data residency and VPC Service Controls. Those controls may be decisive for organizations with location or perimeter requirements. The available documentation does not provide a directly comparable retention statement for individual IDE use, so confirm current terms and privacy documentation before an enterprise purchase or before sending sensitive code through a personal plan.
A practical, low-risk evaluation plan
- Choose a representative repository. Use a non-production project that still contains the languages, build system and test patterns your team uses. Remove secrets and customer data first.
- Define three tasks. Pick one read-only investigation, one multi-file change with tests and one longer task that would benefit from asynchronous or remote execution.
- Test the least-permissive mode. In Cursor, begin with Ask for the investigation. In Antigravity, request a plan artifact before authorizing edits. Compare the accuracy of file discovery and the usefulness of the explanation.
- Measure implementation quality. Give each tool the same acceptance criteria. Record changed files, test results, manual corrections, regressions and time spent reviewing—not just time until the first answer.
- Exercise recovery. Intentionally reject a proposed edit, restore a checkpoint or revert a diff, and verify that your normal version-control workflow remains authoritative.
- Test limits. Note model choices, request counts, weekly resets, credit consumption and what the interface reports when a limit is reached. Do not infer paid-tier capacity from a short free-tier trial.
- Evaluate asynchronous work. For Antigravity, inspect local asynchronous agents and browser artifacts. For Cursor, try a Cloud or Background Agent only in an isolated repository and review its command log and pull-request output.
- Review data flow. List what is indexed, what leaves the workstation, where commands execute and which credentials are available. Have security or legal staff review the current vendor terms for production use.
- Price the real workload. Multiply the seats you need by the published plan price, then add any usage, credit or remote-agent charges you confirm during the trial. Include the cost of human review and infrastructure changes.
Which one fits common workflows?
Choose Antigravity when orchestration is the bottleneck
- Your tasks regularly combine code edits, terminal work and browser interaction.
- You want asynchronous local agents that can continue while you handle another task.
- Plans, diffs, diagrams and recordings are valuable review artifacts for your team.
- You expect to use a desktop app, CLI, extensions or Python SDK rather than one editor surface.
- Google ecosystem integration, regional data residency or VPC Service Controls are important requirements.
Antigravity is less compelling if you only want fast in-editor completion and rarely delegate work outside the current codebase. In that case, its broader surface may add decisions without removing a problem you actually have.
Choose Cursor when editor control is the priority
- Most work happens in one coding editor and involves multi-file changes, tests and diffs.
- You need a clear progression from read-only Ask mode to autonomous Agent mode.
- Checkpoints, Custom modes and existing integrations match your team’s review habits.
- You want optional Cloud or Background Agents for tasks that can run in isolated remote machines.
- A published Teams price of $40 per user per month helps you budget before requesting Enterprise terms.
Cursor is less suitable when your policy forbids remote execution entirely or when browser-centered orchestration is a core requirement. You can keep work local, but the product’s cloud-agent option should be treated as a separate security decision, not as an invisible implementation detail.
For teams deciding between them
Do not standardize solely on individual preference. Select a default based on repository sensitivity, review practice and the proportion of work that benefits from parallel agents. You can permit both during a pilot, but define one policy for indexing, one credential model and one merge gate. Otherwise, the same repository may be exposed to different retention and execution assumptions depending on who opened it.
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Confusing unlimited completions with unlimited agent work
Antigravity’s Individual plan lists unlimited Tab completions and Command requests but still has basic weekly rate limits. Cursor’s free Hobby plan lists limited agent requests and tab completions. Completion volume and autonomous task capacity are different measurements. Track the agent actions that consume your budget.
Best Value
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Assuming all models are included
Antigravity’s free tier provides access to multiple agent models, while paid tiers add higher limits and flexible credits; the exact entitlements are not specified in the snapshot. Cursor plan names alone also do not establish model access. Check the current plan matrix and test the models your codebase requires.
Sending secrets to a remote agent
A background agent that can install dependencies and open a pull request can also encounter hostile instructions. Use a sanitized branch, minimal token scopes, network controls and mandatory review. Never grant production credentials merely to make a development task convenient.
Treating checkpoints or artifacts as version control
Checkpoints, plans and diffs improve review, but they do not replace commits, protected branches, backups or an auditable release process. Keep the repository’s version-control history as the source of truth.
Ignoring retention questions
Privacy Mode and enterprise controls address important parts of data handling, not every part. Ask specifically about plaintext prompts, embeddings, metadata, logs, recordings, regional processing, deletion and model-provider access. If the answer is not in the current terms, record that uncertainty and involve your security owner.
Can you use both?
Yes, a two-tool pilot can reveal which surface matches each class of work. Keep the experiment disciplined: use the same repository snapshot, acceptance tests and permissions; label which agent produced each change; and compare review time as well as output quality.
A practical division is to use the editor-centered tool for routine code navigation and controlled multi-file edits, while reserving the agent-first environment for tasks that need browser interaction, diagrams or asynchronous orchestration. That division should be based on observed fit, not on a promise that one product is universally better.
Before adopting both, settle repository-level rules for indexing, remote execution, secrets and pull-request review. A mixed toolchain without shared controls can create more security variance than either product alone.
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Antigravity is the stronger match for an agent-first workflow that spans editor, terminal and browser and produces explicit artifacts for asynchronous collaboration. Cursor is the stronger match for an editor-first workflow that values selectable autonomy, checkpoints, integrations and a transparent team price. Start with both free tiers on the same sanitized project, measure real agent work and review burden, then choose the plan whose limits, model access and data controls fit your workload.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
