Compare Google ADK with top alternatives in the agent framework category. Find detailed side-by-side comparisons to help you choose the best tool for your needs.
These tools are commonly compared with Google ADK and offer similar functionality.
AI Agents
Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.
AI agent framework
LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.
Multi-Agent Builders
Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.
AI Agent Builders
AWS open-source SDK for building AI agents in Python and TypeScript with model-driven tool orchestration, multi-provider LLM support, and native AWS deployment options.
AI Agent Builders
OpenAI Agents SDK is an open-source Python framework for building agentic apps with handoffs, guardrails, sessions, tracing, MCP tools, sandbox agents, and realtime voice agents.
Other tools in the agent framework category that you might want to compare with Google ADK.
Agent framework
Microsoft’s framework for creating interoperable agents and graph-based AI workflows.
Agent framework
Open-source LangChain framework for agents that plan, manage files and delegate.
💡 Pro tip: Most tools offer free trials or free tiers. Test 2-3 options side-by-side to see which fits your workflow best.
ADK is more opinionated and ships with a built-in evaluation framework, local debugging UI, and structured workflow agent types (sequential, parallel, loop) out of the box, whereas LangChain/LangGraph are more flexible and modular with a larger third-party ecosystem. ADK also provides four official language SDKs (Python, TypeScript, Go, Java) versus LangChain's Python and JavaScript. Choose ADK for structured multi-agent development with Google Cloud integration; choose LangChain/LangGraph for maximum flexibility and community ecosystem breadth.
Yes. ADK supports any LLM through LiteLLM integration, and the documentation explicitly lists Anthropic Claude, Ollama, vLLM, LiteRT-LM, and Apigee AI Gateway as supported model providers alongside Gemini and Gemma. However, some Gemini-optimized features like built-in Google Search grounding are only available when using Google models.
No. ADK runs entirely locally for development and includes a local web UI, CLI, and API server runtime. You can also deploy to any container platform including Cloud Run, GKE, or non-Google clouds via standard Docker containers. Google Cloud and Vertex AI Agent Engine are optional managed deployment targets, not requirements.
ADK ships in four official SDKs: Python (currently 2.0 Beta with workflow agents and agent teams), TypeScript 1.0 (newly released in 2026 — making ADK one of the few enterprise agent frameworks with first-party TypeScript support), Go, and Java. The Python 2.0 Beta introduces new workflow primitives, ambient agents, resumable runs, and cancelable execution.
ADK ships with a comprehensive evaluation framework that includes criteria-based scoring, user simulation (synthetic user interactions), environment simulation (mocked tools and external systems), and custom metrics. It also offers an optimization module for iterative improvement, allowing teams to systematically test and refine agent quality before production deployment.
Compare features, test the interface, and see if it fits your workflow.