Pick AutoGen if
engineers prototyping multi-agent apps who want a canvas before they commit to YAML.
Read the AutoGen pageAutoGen vs Langflow
Our take
Pick AutoGen if engineers prototyping multi-agent apps who want a canvas before they commit to YAML. Pick Langflow if developers and applied-AI teams who want a visual LangChain-style graph they can still edit as Python. Skip AutoGen if people who want a hosted research composer (Elicit) or a visual LLM app studio with a Cloud SKU (Dify). Skip Langflow if non-technical ops teams that need Slack/HubSpot glue, or
Best for
AutoGen Compose a team of agents and run them
Langflow Prototyping an agent
Free plan
AutoGen $0 · mIT code. You bring an LLM API key or a local model
Langflow $0 · no license fee (MIT). You run uv pip install langflow or Docker. You pay your own LLM/provider bills
Lowest paid
AutoGen Not published by the vendor
Langflow Not published by the vendor
Coding agent
AutoGen Agents / models / tools / terminations
Langflow Visual agent canvas
Runs where
AutoGen Hosted
Langflow Local; you host it
Watch out
AutoGen Studio is not “free AI.”
Langflow You bring the model key
Last checked
AutoGen 2026-10-19 · microsoft.github.io/autogen/stable/user-guide
Langflow 2026-10-19 · docs.langflow.org/get-started-installation
Which one, then?
Pick Langflow if
developers and applied-AI teams who want a visual LangChain-style graph they can still edit as Python.
Read the Langflow page