Comparisons / CAMEL AI vs Google ADK

CAMEL AI vs Google ADK: Which Agent Framework to Use?

CAMEL AI vs Google ADK, head to head

CAMEL AI 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.

CAMEL AI pioneered role-playing multi-agent conversations in a 2023 NeurIPS paper.

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 CAMEL AI if

Pick CAMEL AI if cAMEL AI's research contribution — role-playing and inception prompting — is a genuinely useful technique for reducing hallucination through multi-agent debate. But the technique is the value, not the framework. Two LLM calls with different system prompts give you the same pattern 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 CAMEL AIcomparison →

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; CAMEL AI 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. CAMEL AI 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

CAMEL AI

GitHub Stars

16.6k

Forks

1.9k

Language

Python

License

Apache-2.0

Created

2023-03-17

Created by

CAMEL-AI.org (King Abdullah University)

github.com/camel-ai/camel

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.

ConceptCAMEL AIGoogle ADK
Agent`ChatAgent` with `role_name`, `role_type`, and `system_message` for behavior`LlmAgent` class with model, instructions, and `sub_agents` list
ToolsTool modules registered on agents with OpenAI-compatible function schemas`FunctionTool`, built-in tools (Search, Code Exec), third-party integrations
Role-Playing`RolePlaying` session with `user_agent`, `assistant_agent`, and inception prompting
Inception PromptingSystem prompts that embed the task, roles, and constraints to prevent drift
SocietyMulti-agent societies with role assignment, communication, and voting
Task DecompositionAI Society that splits tasks into subtasks assigned to specialist role pairs
Agent Loop`Runner.run()` with automatic tool dispatch and sub-agent delegation
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 CAMEL AI 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 →