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 OpenAI Agents SDK vs LangGraph by community traction (★ 40k vs ★ 29k). Pick OpenAI Agents SDK for minimal orchestration; pick LangGraph for stateful multi-agent workflows.
✓ Live data verified
| OpenAI Agents SDK | LangGraph | |
|---|---|---|
| GitHub stars | ★ 29k | ★ 40k |
| Language | Python | Python |
| Category | Agent frameworks | Agent frameworks |
| Best for | minimal orchestration | stateful multi-agent workflows |
| Repository | openai/openai-agents-python | langchain-ai/langgraph |
OpenAI Agents SDK and LangGraph are both credible choices. By community traction, LangGraph leads (★ 40k). Pick OpenAI Agents SDK for minimal orchestration; pick LangGraph for stateful multi-agent workflows.
Both are credible agent frameworks. By community traction LangGraph leads (★ 40k). Pick OpenAI Agents SDK for minimal orchestration; pick LangGraph for stateful multi-agent workflows.
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 is Graph-based orchestration for stateful, multi-actor agent workflows with explicit control flow and checkpointing..
LangGraph has more — ★ 40k vs ★ 29k (live counts).
Often yes — many teams combine agent frameworks. Check each tool's docs for interop; they solve overlapping but not identical problems.
OpenAI Agents SDK is primarily Python; LangGraph is primarily Python.
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