AutoGen vs Langflow
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. Langflow suits teams needing open-source access, visual builder focus, and 153,543 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 | Langflow |
|---|---|---|
| GitHub Stars | 60.6K | 153.5K |
| Contributors | 444 | 351 |
| Last Commit | Apr 15, 2026 | Aug 22, 2026 |
| Open Issues | 997 | 968 |
| 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 has a larger visible contributor base (444 vs 351).
- • AutoGen is the cleaner fit if you specifically need Microsoft workflows from the catalog tags.
Choose Langflow if you need
- • Langflow is the stronger pick when Visual Builder matters because that capability is listed only on its profile.
- • Langflow shows broader GitHub adoption with 153,543 stars versus 60,568 for AutoGen.
- • Langflow is the cleaner fit if you specifically need Visual Builder workflows from the catalog tags.
Meaningful differences
- • GitHub adoption: AutoGen shows 60,568 stars versus 153,543 for Langflow.
- • Contributor count: AutoGen lists 444 contributors and Langflow lists 351.
Shared capabilities
- • Multi Agent
- • Python
Shared Tags
Only in AutoGen
Only in Langflow
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 Langflow
Langflow is a visual framework for building multi-agent and RAG applications. Its drag-and-drop interface lets you create complex agent workflows without code, while still allowing Python customization. Supports all major LLM providers, vector stores, and tools. Export flows as APIs with one click. The most popular visual agent builder.
View full listing