A side-by-side of two agent frameworks for building AI agents — live GitHub data, languages, and what each is best at.
Short answer: LangGraph leads LangGraph vs OpenAI Agents SDK by community traction (★ 42k vs ★ 30k). Pick LangGraph for stateful multi-agent workflows; pick OpenAI Agents SDK for minimal orchestration.
✓ Live data verified
| LangGraph | OpenAI Agents SDK | |
|---|---|---|
| GitHub stars | ★ 42k | ★ 30k |
| Language | Python | Python |
| Category | Agent frameworks | Agent frameworks |
| Best for | stateful multi-agent workflows | minimal orchestration |
| Repository | langchain-ai/langgraph | openai/openai-agents-python |
LangGraph and OpenAI Agents SDK are both credible choices. By community traction, LangGraph leads (★ 42k). Pick LangGraph for stateful multi-agent workflows; pick OpenAI Agents SDK for minimal orchestration.
Both are credible agent frameworks. By community traction LangGraph leads (★ 42k). Pick LangGraph for stateful multi-agent workflows; pick OpenAI Agents SDK for minimal orchestration.
LangGraph is Graph-based orchestration for stateful, multi-actor agent workflows with explicit control flow and checkpointing.. OpenAI Agents SDK is OpenAI's lightweight agent framework — a small set of primitives (Agents, Handoffs, Guardrails, Sessions); provider-agnostic via LiteLLM. Evolved from Swarm..
LangGraph has more — ★ 42k vs ★ 30k (live counts).
Often yes — many teams combine agent frameworks. Check each tool's docs for interop; they solve overlapping but not identical problems.
LangGraph is primarily Python; OpenAI Agents SDK is primarily Python.
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