langchain-ai/langgraph vs openai/openai-agents-python
langchain-ai/langgraph scores higher overall: 82/100 (A-tier) against 79/100 (A-tier). langchain-ai/langgraph leads on reliability, skill leverage, evaluation readiness; openai/openai-agents-python leads on no dimension. Scored 2026-07-07, methodology v1.0.
Dimension by dimension
| Dimension | langgraph | openai-agents-python |
|---|---|---|
| Reliability | 80 | 78 |
| Skill Leverage | 82 | 76 |
| Documentation | 84 | 84 |
| Maintenance | 92 | 92 |
| Safety / Governance | 72 | 72 |
| Evaluation Readiness | 76 | 70 |
| Composability | 80 | 78 |
| Adoption (capped) | 90 | 86 |
| Overall | 82 · A | 79 · A |
The entries
The most adopted graph-based agent orchestration framework: workflows as explicit state machines with checkpointing, human-in-the-loop…
OpenAI's first-party multi-agent framework: agents, handoffs, guardrails, and tracing in a deliberately small API surface.
Frequently asked questions
langchain-ai/langgraph or openai/openai-agents-python?
langchain-ai/langgraph scores higher overall (82 vs 79, methodology v1.0). But they are the same category, so the dimension table below is the real answer.
How is this comparison generated?
Both scorecards come from the same public rubric with evidence notes, scored by the same editorial process. This page presents them side by side; it adds no new judgments beyond the scores themselves.