Comparisons / Google ADK vs OpenAI Agents SDK

Google ADK vs OpenAI Agents SDK: Which Agent Framework to Use?

Google's Agent Development Kit (ADK) is an open-source framework for building multi-agent systems. OpenAI's Agents SDK (evolved from Swarm) provides Agent, Runner, handoffs, and guardrails. Here is how they compare — paradigm, ecosystem, and the use cases each one is actually built for.

By the numbers

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

OpenAI Agents SDK

GitHub Stars

20.6k

Forks

3.4k

Language

Python

License

MIT

Created

2025-03-11

Created by

OpenAI

github.com/openai/openai-agents-python

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

ConceptGoogle ADKOpenAI Agents SDK
Agent`LlmAgent` class with model, instructions, and `sub_agents` list`Agent(name, instructions, model, tools)`
Tools`FunctionTool`, built-in tools (Search, Code Exec), third-party integrationsPython functions with type hints, auto-converted to schemas
Agent Loop`Runner.run()` with automatic tool dispatch and sub-agent delegation`Runner.run()` handles the loop internally
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
Handoffs`Handoff` between `Agent` objects for multi-agent routing
Guardrails`InputGuardrail` and `OutputGuardrail` with tripwire pattern
ContextTyped context object passed through the agent lifecycle

Google ADK vs OpenAI Agents SDK, head to head

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

OpenAI Agents SDK OpenAI's Agents SDK (evolved from Swarm) provides Agent, Runner, handoffs, and guardrails.

Both wrap the same underlying agent pattern — an LLM call, a tool dispatch, a loop — in different abstractions. The choice between them is mostly about which mental model and ecosystem fits the team you have, not which one is technically more capable.

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. Google ADK is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; OpenAI Agents SDK would force you to translate.

Full Google ADK comparison →

Pick OpenAI Agents SDK if

Pick OpenAI Agents SDK if the Agents SDK is the thinnest framework on this list — it barely abstracts beyond what you'd write yourself. Use it when you want OpenAI's conventions and auto-schema generation. Skip it when you want full control or use non-OpenAI models. OpenAI Agents SDK is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Google ADK would force you to translate.

Full OpenAI Agents SDK comparison →

What both add

Both Google ADK and OpenAI Agents SDK pull in a class hierarchy and a dependency tree to wrap what is, at the core, an HTTP POST in a while loop. If your use case is straightforward — one provider, a handful of tools, a single agent — the framework cost may exceed the framework benefit. The lesson below shows the same pattern in ~60 lines without either dependency.

Or build your own in 60 lines

Both Google ADK and OpenAI Agents SDK 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 →