Comparisons / CrewAI vs OpenAI Agents SDK

CrewAI vs OpenAI Agents SDK: Which Agent Framework to Use?

CrewAI organizes work into Agents, Tasks, and Crews. 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

CrewAI

GitHub Stars

48.0k

Forks

6.5k

Language

Python

License

MIT

Created

2023-10-27

Created by

João Moura

github.com/crewAIInc/crewAI

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.

ConceptCrewAIOpenAI Agents SDK
Agent`Agent(role, goal, backstory, tools, llm)``Agent(name, instructions, model, tools)`
ToolsTool registration with `@tool` decorator, custom `Tool` classesPython functions with type hints, auto-converted to schemas
Agent LoopInternal to `Agent` execution, hidden from user`Runner.run()` handles the loop internally
Task Delegation`Crew(agents, tasks, process=sequential/hierarchical)`
Memory`ShortTermMemory`, `LongTermMemory`, `EntityMemory`
StateTask output passed between agents via `Crew` orchestration
Handoffs`Handoff` between `Agent` objects for multi-agent routing
Guardrails`InputGuardrail` and `OutputGuardrail` with tripwire pattern
ContextTyped context object passed through the agent lifecycle

CrewAI vs OpenAI Agents SDK, head to head

CrewAI CrewAI organizes work into Agents, Tasks, and Crews.

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 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. CrewAI 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 CrewAIcomparison →

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; CrewAI would force you to translate.

Full OpenAI Agents SDKcomparison →

What both add

Both CrewAI 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 CrewAI 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 →