AutoGen vs LangGraph
Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.
Direct Answer
AutoGen suits teams needing open-source access, conversation focus, and 60,568 GitHub stars in current listing data. LangGraph suits teams needing open-source access, typescript focus, and 40,209 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.
What this comparison weighs
- Pricing and free-tier availability
- License model and deployment fit
- GitHub adoption and contributor depth
- Catalog tags, integrations, and supported workflows
| Metric | AutoGen | LangGraph |
|---|---|---|
| GitHub Stars | 60.6K | 40.2K |
| Contributors | 444 | 278 |
| Last Commit | Apr 15, 2026 | Aug 22, 2026 |
| Open Issues | 997 | 708 |
| License | open-source | open-source |
| Pricing | open-source | open-source |
| Free Tier | Yes | Yes |
| Category | frameworks | frameworks |
| Trending | No | No |
Choose AutoGen if you need
- • AutoGen is the stronger pick when Conversation matters because that capability is listed only on its profile.
- • AutoGen shows broader GitHub adoption with 60,568 stars versus 40,209 for LangGraph.
- • AutoGen has a larger visible contributor base (444 vs 278).
Choose LangGraph if you need
- • LangGraph stands out for Typescript workflows that are not listed for AutoGen.
- • LangGraph is the stronger pick when Graph matters because that capability is listed only on its profile.
- • LangGraph is the cleaner fit if you specifically need Graph workflows from the catalog tags.
Meaningful differences
- • Workflow emphasis: AutoGen highlights Python, while LangGraph highlights Typescript.
- • GitHub adoption: AutoGen shows 60,568 stars versus 40,209 for LangGraph.
- • Contributor count: AutoGen lists 444 contributors and LangGraph lists 278.
Shared capabilities
- • Multi Agent
- • Python
- • Human In The Loop
Shared Tags
Only in AutoGen
Only in LangGraph
Limitations and evidence
- • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
- • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
- • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.
About AutoGen
AutoGen is Microsoft's open-source framework for building multi-agent conversational systems where agents can converse with each other and with humans to solve complex tasks. Agents are highly customizable and can use LLMs, tools, and human input in flexible combinations. The framework supports group chats, nested conversations, and code execution sandboxes, making it well-suited for coding assistants, research automation, and enterprise agentic workflows. AutoGen Studio provides a no-code UI for prototyping agent systems visually.
View full listingAbout LangGraph
LangGraph is LangChain's framework for building stateful, multi-actor agent applications as graphs. Define agents as nodes and their interactions as edges, with built-in persistence, streaming, human-in-the-loop, and time-travel debugging. The standard for production agent orchestration in the LangChain ecosystem.
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