Google Agent Development Kit (ADK) vs Google Antigravity

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Google Agent Development Kit (ADK) Agents	Google Antigravity Agents
Tagline	Google's open-source framework for building, evaluating, and deploying production AI agents	Google's agent-first development platform for building software with autonomous coding agents.
Category	Agents	Agents
Pricing	Free· Framework itself is free and open-source (Apache 2.0). Costs come from the underlying model provider (e.g. Gemini API / Vertex AI usage) and any hosting infrastructure (Cloud Run, GKE, Agent Engine).	Freemium· For Individuals: $0/month · Google AI Pro: ? · Google AI Ultra: ? · Organization plan via Google Cloud: ?
Model	Gemini (default) plus Claude, GPT-4/5, Llama, and other providers via LiteLLM	Gemini 3 family (Flash tiers highlighted)
Editorial score	—	—
Use cases	Multi-agent research assistantCustomer support triage agentRAG chatbot backed by Vertex AI SearchCode review and refactoring agentBigQuery natural-language analytics agentDocument processing pipelineVoice/streaming conversational agentInternal tool-use agent orchestrating APIsEvaluation and regression testing of LLM workflowsEnterprise workflow automation on Agent Engine	Parallel autonomous coding agentsRepository-aware refactorsScheduled dependency upgradesAutomated test backfillsMulti-step migration agentsAgentic pair programming in an IDEHeadless CLI coding runs in CICustom Python agent prototypingInternal engineering-chore automationEnterprise agent orchestration
Pros	Genuinely open-source (Apache 2.0) with active Google engineering behind it, not a hosted-only product Multi-language: first-class Python, Java, and Go SDKs — rare among agent frameworks that are usually Python-only Built-in dev UI (`adk web`) with trace inspection, event stream, and session replay speeds up debugging enormously Model-agnostic via LiteLLM — Gemini is default but Claude, GPT, and local models plug in cleanly Rich multi-agent primitives out of the box: SequentialAgent, ParallelAgent, LoopAgent, and hierarchical sub-agents Tight Google Cloud integration for deployment (Cloud Run, GKE, Agent Engine) plus native BigQuery/Vertex Search tools Evaluation harness with trajectory-level scoring is included, not a separate paid add-on First-class MCP (Model Context Protocol) client and server support	Ships as a full stack — desktop command center, IDE, CLI, and Python SDK — not just an editor plugin Designed from the ground up to supervise multiple autonomous agents running in parallel on the same repo Built-in scheduling turns recurring engineering chores (upgrades, sweeps, backfills) into cron-like agent tasks Free for individual developers, lowering the barrier vs paid seats on Cursor / Copilot Business First-party access to Google's Gemini 3 family with the model tuning and quota that come from being Google Python SDK makes it straightforward to prototype custom agents and wire them into existing internal tooling
Cons	Documentation and examples lean heavily on Gemini + Google Cloud; non-Google paths work but feel like second-class citizens API surface is still evolving — breaking changes between minor versions have been common through 2025-2026 Multi-agent orchestration primitives are powerful but the graph/callback model has a real learning curve compared to a plain prompt loop Agent Engine deployment is convenient but locks you into GCP billing and quotas TypeScript/Kotlin support lags the Python SDK in features and community examples	Very new — expect churn in APIs, agent behavior, and pricing before it stabilizes Public docs are thin on model routing, per-tier limits, data handling, and exactly what runs locally vs in Google cloud Downloads highlighted on the site are macOS-first; Windows and Linux coverage is less clearly advertised Ties you to Google's Gemini defaults; multi-provider model choice is less front-and-center than in Cursor or Cline 'Free' tier without published quotas makes it hard to plan around future paid gating Autonomous multi-agent workflows still need careful human review — hallucinated edits and runaway commands are a real risk
Website	google.github.io	antigravity.google

Pick Google Agent Development Kit (ADK) if

✅ Genuinely open-source (Apache 2.0) with active Google engineering behind it, not a hosted-only product
✅ Multi-language: first-class Python, Java, and Go SDKs — rare among agent frameworks that are usually Python-only
✅ Built-in dev UI (`adk web`) with trace inspection, event stream, and session replay speeds up debugging enormously
✅ Model-agnostic via LiteLLM — Gemini is default but Claude, GPT, and local models plug in cleanly

Pick Google Antigravity if

✅ Ships as a full stack — desktop command center, IDE, CLI, and Python SDK — not just an editor plugin
✅ Designed from the ground up to supervise multiple autonomous agents running in parallel on the same repo
✅ Built-in scheduling turns recurring engineering chores (upgrades, sweeps, backfills) into cron-like agent tasks
✅ Free for individual developers, lowering the barrier vs paid seats on Cursor / Copilot Business

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