crewai vs openai-agents-python
Two of the top projects in Agent frameworks and SDKs, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
crewai
Python framework for multi-agent workflows with role-based Crews and event-driven Flows
openai-agents-python
Python SDK for multi-agent workflows with handoffs, guardrails and tracing
Verdict
crewai ranks higher, 80 to 77. Of the 4 score parts we measure for both, crewai leads on 1, openai-agents-python on 2 and 1 is even.
- Adoptioncrewai leads by 41 points, 75 to 34: a wide gap.
- FreshnessEven at 100.
- Maintenanceopenai-agents-python leads by 17 points, 99 to 82: a wide gap.
- Agent-readyopenai-agents-python leads by 40 points, 70 to 30: a wide gap.
Pick crewai if you are
Python developers building multi-agent LLM workflows in code
- Two models: autonomous Crews and explicit Flows with state, branching and or_/and_ triggers
- CLI scaffolds projects; agents and tasks declared in JSONC or classic YAML
Pick openai-agents-python if you are
Python developers building tool-using or multi-agent LLM apps
- Small API: Agent and Runner cover a text agent in a few lines
- Tools can be Python functions, MCP servers or hosted tools
| What we compare | crewai | openai-agents-python |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 75, popular | 34, known |
| Freshness | 100, active | 100, active |
| Maintenance | 82, healthy | 99, healthy |
| Easy to run | Not scored for this kind | Not scored for this kind |
| Agent-ready | 30, minimal | 70, partly |
| Facts from GitHub and the README | ||
| Stars | 59.7k | 30k |
| License | MIT (permissive) | MIT (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Python | Python |
| Docker | No | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
crewai
CrewAI is a Python framework for building multi-agent workflows. Crews are teams of role-based agents with goals, tools and tasks, run sequentially or under a hierarchical manager. Flows are event-driven workflows with typed state, branching and routing that can embed Crews. A CLI scaffolds JSON-defined crew projects, with a classic YAML scaffold still available.
Who it is for: Python developers building multi-agent LLM workflows in code
Strengths
- Two models: autonomous Crews and explicit Flows with state, branching and or_/and_ triggers
- CLI scaffolds projects; agents and tasks declared in JSONC or classic YAML
- Covers tools, memory, knowledge, checkpointing, async execution and MCP/A2A support
- MIT license; recent commit and release within days of listing
Weaknesses
- Managed deployment, governance and enterprise support are in the commercial AMP Suite
- README has a telemetry section; opt-out details are not in the excerpt
- Requires Python >=3.10 and <3.14 and uv; Windows may need C++ build tools
- Web search example needs a separate Serper.dev API key
- no GPU
- Needs Python >=3.10,<3.14, uv, LLM provider API key, Serper.dev API key (optional, web search)
- Models: OpenAI (e.g. openai/gpt-4o), other providers via LLM setup
openai-agents-python
Python library from OpenAI for building agents with instructions, tools, guardrails and handoffs between agents. It supports the OpenAI Responses and Chat Completions APIs and, per the README, 100+ other LLMs. It also includes sandbox agents, realtime and voice agents, sessions for conversation history, human-in-the-loop controls and built-in tracing.
Who it is for: Python developers building tool-using or multi-agent LLM apps
Strengths
- Small API: Agent and Runner cover a text agent in a few lines
- Tools can be Python functions, MCP servers or hosted tools
- Built-in tracing, guardrails, sessions and human-in-the-loop support
- Includes sandbox, realtime and voice agents; MIT license, Python 3.10+
Weaknesses
- Examples assume OPENAI_API_KEY; non-OpenAI models go through optional LiteLLM or any-llm
- Pull requests limited to repository collaborators
- Python only; JS/TS version is a separate repository
- Realtime agents use gpt-realtime-2.1, an OpenAI-hosted model
- no GPU
- Needs OpenAI API key, Python 3.10+, optional: Redis, optional: SQLAlchemy, optional: websockets, optional: LiteLLM or any-llm, optional: Docker
- Models: OpenAI Responses API, OpenAI Chat Completions API, 100+ other LLMs via LiteLLM or any-llm
More in Agent frameworks and SDKs
Building with these?
We help teams pick an open-source AI stack and run it in production. Client work never changes a rank.