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Google Antigravity 2.0 vs Kastor (2026)

A side-by-side comparison of Google Antigravity 2.0 and Kastor on pricing, features, and fit, so you can decide which is right for you.

Last updated: July 16, 2026

Quick answer

Google Antigravity 2.0 and Kastor are both strong choices, but they fit different needs. Choose Google Antigravity 2.0 if you mainly need building automated research pipelines using multiple specialized ai agents — its edge is desktop-native interface gives developers more control and faster iteration cycles. Choose Kastor if you need building multi-step research assistants that delegate subtasks to specialized sub-agents — its edge is completely free and open-source with no licensing fees or usage limits. Google Antigravity 2.0 starts at Pricing details not publicly confirmed; check official site for plans; Kastor starts at Free.

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Google Antigravity 2.0 logo
Google Antigravity 2.0

Orchestrate powerful multi-agent AI workflows from your desktop.

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Kastor logo
Kastor

Build and coordinate powerful multi-agent AI systems with ease.

PricingFreemium
PricingFree
Starts atPricing details not publicly confirmed; check official site for plans
Starts atFree
Free tierFree tier available with basic agent orchestration features
Free tierFully free and open-source
RatingNot yet rated
RatingNot yet rated
Best forBuilding automated research pipelines using multiple specialized AI agents
Best forBuilding multi-step research assistants that delegate subtasks to specialized sub-agents
Key strengthDesktop-native interface gives developers more control and faster iteration cycles
Key strengthCompletely free and open-source with no licensing fees or usage limits
Main drawbackLimited public documentation makes it hard to assess full capabilities before downloading
Main drawbackRequires developer expertise to set up and configure compared to managed platforms

Features compared

Google Antigravity 2.0

  • Visual multi-agent workflow orchestration from a native desktop application
  • Support for coordinating parallel AI agent tasks and pipelines
  • Local-first environment for testing and debugging agent interactions
  • Integration capabilities with Google AI services and third-party tools

Kastor

  • Multi-agent orchestration framework for coordinating multiple AI agents simultaneously
  • Open-source codebase with full transparency and community-driven development
  • Extensible architecture supporting custom LLM backends and tool integrations
  • Agent communication and context-sharing protocols for collaborative task execution

Pros & cons

Google Antigravity 2.0

Pros

  • Desktop-native interface gives developers more control and faster iteration cycles
  • Local orchestration improves privacy and security for sensitive workflows
  • Backed by Google infrastructure, suggesting strong reliability and ecosystem integration

Cons

  • Limited public documentation makes it hard to assess full capabilities before downloading
  • As a newer release, community support and third-party integrations may still be maturing

Kastor

Pros

  • Completely free and open-source with no licensing fees or usage limits
  • Gives developers full control over agent logic, memory, and integrations
  • Active open-source community enables rapid iteration and community-contributed extensions

Cons

  • Requires developer expertise to set up and configure compared to managed platforms
  • Documentation and support may be limited compared to commercial multi-agent frameworks

The verdict

Choose Google Antigravity 2.0 if

you mainly need to building automated research pipelines using multiple specialized ai agents. Its edge: desktop-native interface gives developers more control and faster iteration cycles.

Choose Kastor if

you mainly need to building multi-step research assistants that delegate subtasks to specialized sub-agents. Its edge: completely free and open-source with no licensing fees or usage limits.

Frequently asked questions

Is Google Antigravity 2.0 better than Kastor?

Neither is universally better. Google Antigravity 2.0 is stronger for building automated research pipelines using multiple specialized ai agents, with an edge in desktop-native interface gives developers more control and faster iteration cycles. Kastor is stronger for building multi-step research assistants that delegate subtasks to specialized sub-agents, with an edge in completely free and open-source with no licensing fees or usage limits. Pick based on your main task.

Which is cheaper, Google Antigravity 2.0 or Kastor?

Google Antigravity 2.0 starts at Pricing details not publicly confirmed; check official site for plans and Kastor starts at Free. Free tier: Google Antigravity 2.0 — Free tier available with basic agent orchestration features; Kastor — Fully free and open-source.

What is Google Antigravity 2.0 best for?

Google Antigravity 2.0 is best for building automated research pipelines using multiple specialized ai agents, coordinating complex software development workflows with agent-based task delegation, prototyping and testing multi-agent systems before deploying to production cloud environments.

What is Kastor best for?

Kastor is best for building multi-step research assistants that delegate subtasks to specialized sub-agents, automating complex workflows where multiple ai agents must collaborate and hand off results, prototyping agentic pipelines for startups or research teams without incurring api or platform costs.

Do Google Antigravity 2.0 and Kastor have free plans?

Google Antigravity 2.0: Free tier available with basic agent orchestration features. Kastor: Fully free and open-source. Check each tool's pricing page for current limits, as plans change.