No editorial guesswork — every number below comes straight from the GitHub REST API and PyPI download-stats API, queried live. Here's how LangChain/LangGraph, CrewAI, OpenAI Agents SDK, Google ADK, and Microsoft AutoGen actually stack up.
Click any column header to sort. Figures are monthly totals as of the snapshot date.
| Framework ▲ | GitHub Stars ▲ | Downloads / Month ▲ | Positioning ▲ | Best For ▲ |
|---|---|---|---|---|
| LangChain / LangGraph142,051 + 37,574 stars | 179,625combined | 319.5M319,543,039 | Runtime + stateful orchestration layer — "the agent engineering platform" | Default starting point for most agent-building projects |
| Microsoft AutoGen59,810 stars | 59,810 | 1.03M1,031,292 | Research-grade multi-agent conversation framework | Academic / research experimentation with multi-agent dialogue |
| CrewAI55,751 stars | 55,751 | 11.0M10,994,928 | Role-based "crew of agents" collaborative orchestration | Fastest-growing framework-agnostic tool; multi-role agent teams |
| Google ADK20,658 stars | 20,658 | 15.6M15,577,110 | Code-first Python toolkit for building, evaluating & deploying agents | Enterprise on-ramp tied to Vertex AI / Gemini |
| OpenAI Agents SDK27,994 stars | 27,994 | 31.3M31,343,492 | Lightweight, powerful framework for multi-agent workflows | Teams building directly on OpenAI models |
Sortable table — click a column header to sort ascending/descending.
What each one is, who it's for, and where it's winning.
The agent engineering platform, split into a runtime (LangChain) and a stateful orchestration layer (LangGraph) for building resilient agents.
Best for: teams that want the most battle-tested, widely-adopted default entry point into agent building, with the largest ecosystem of integrations.
View on GitHub →Role-based "crew of agents" abstraction for collaborative, multi-agent orchestration — the freshest commit activity of the top five.
Best for: teams designing multi-agent "crews" with distinct roles and responsibilities, and who want the fastest-growing framework-agnostic option.
View on GitHub →A lightweight, powerful framework for multi-agent workflows with the second-highest download volume of all five — despite the smallest star count.
Best for: teams building directly on OpenAI models who want a native, minimal-overhead SDK instead of a third-party abstraction layer.
View on GitHub →A code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents — Google's enterprise on-ramp for agentic AI.
Best for: enterprise teams already on Vertex AI / Gemini who want an officially-supported, evaluation-first agent toolkit.
View on GitHub →A research-driven multi-agent conversation framework with strong academic reputation, but the weakest recent commit and download momentum of the top five.
Best for: academic and research settings exploring multi-agent conversation patterns, though production teams should note the last push was April 2026.
View on GitHub →