Comparisons / CrewAI vs Google ADK

CrewAI vs Google ADK: Which Agent Framework to Use?

CrewAI vs Google ADK, head to head

CrewAI and Google ADK both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.

CrewAI organizes work into Agents, Tasks, and Crews.

Google's Agent Development Kit (ADK) is an open-source framework for building multi-agent systems.

Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.

Pick CrewAI if

Pick CrewAI if crewAI shines for multi-agent setups where you want named roles ("researcher", "writer"). But the core mechanics — tool dispatch, the agent loop, task scheduling — are the same patterns you can build in plain Python. The tradeoffs in its intro should match how your team already thinks about agents; Google ADK will feel like translation if they don't.

Full CrewAIcomparison →

Pick Google ADK if

Pick Google ADK if aDK earns its complexity when you need multi-agent orchestration on Google Cloud with Vertex AI deployment. If you're using Gemini and need production-grade agent infrastructure, it's well-designed. For single-agent use cases or non-Google stacks, plain Python keeps things simpler. The tradeoffs in its intro should match how your team already thinks about agents; CrewAI will feel like translation if they don't.

Full Google ADKcomparison →

What both add

Whichever you pick, you're inheriting a dependency tree and a vocabulary your team has to learn before they ship anything. CrewAI has its own class hierarchy and tool registration conventions; Google ADK has its. Either way, when something misbehaves you'll be reading framework source before you reach the actual HTTP call.

If the real workload is one model and a handful of tools, both can feel like a workbench for driving a nail. The lesson below builds the same pattern in plain Python — useful as a comparison point even if you ultimately keep the framework.

By the numbers

By the numbers

CrewAI

GitHub Stars

48.0k

Forks

6.5k

Language

Python

License

MIT

Created

2023-10-27

Created by

João Moura

github.com/crewAIInc/crewAI

Google ADK

GitHub Stars

18.7k

Forks

3.2k

Language

Python

License

Apache-2.0

Created

2025-04-01

Created by

Google

Backed by

Google/Alphabet

Cloud/SaaS

Vertex AI

Production ready

Yes

github.com/google/adk-python

GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.

ConceptCrewAIGoogle ADK
Agent`Agent(role, goal, backstory, tools, llm)``LlmAgent` class with model, instructions, and `sub_agents` list
ToolsTool registration with `@tool` decorator, custom `Tool` classes`FunctionTool`, built-in tools (Search, Code Exec), third-party integrations
Agent LoopInternal to `Agent` execution, hidden from user`Runner.run()` with automatic tool dispatch and sub-agent delegation
Task Delegation`Crew(agents, tasks, process=sequential/hierarchical)`
Memory`ShortTermMemory`, `LongTermMemory`, `EntityMemory`
StateTask output passed between agents via `Crew` orchestration
Multi-AgentHierarchical agent tree with root agent delegating to specialized sub-agents
Workflows`SequentialAgent`, `ParallelAgent`, `LoopAgent` workflow primitives
SessionSession and State service with typed channels and persistence

Or build your own in 60 lines

Both CrewAI and Google ADK implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.

No framework. No dependencies. No opinions. Just the code.

Build it from scratch →