google/adk-python vs langchain-ai/langgraph
langchain-ai/langgraph scores higher overall: 82/100 (A-tier) against 78/100 (A-tier). google/adk-python leads on safety, evaluation readiness; langchain-ai/langgraph leads on reliability, skill leverage, documentation. Scored 2026-07-07, methodology v1.0.
Dimension by dimension
| Dimension | google-adk | langgraph |
|---|---|---|
| Reliability | 74 | 80 |
| Skill Leverage | 76 | 82 |
| Documentation | 80 | 84 |
| Maintenance | 92 | 92 |
| Safety / Governance | 74 | 72 |
| Evaluation Readiness | 78 | 76 |
| Composability | 74 | 80 |
| Adoption (capped) | 84 | 90 |
| Overall | 78 · A | 82 · A |
The entries
Google's Agent Development Kit: code-first agent construction with built-in evaluation tooling and deployment paths into the Google Cloud…
The most adopted graph-based agent orchestration framework: workflows as explicit state machines with checkpointing, human-in-the-loop…
Frequently asked questions
google/adk-python or langchain-ai/langgraph?
langchain-ai/langgraph scores higher overall (82 vs 78, 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.