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Comparison

autogen vs LLFn

Verdict

Pick autogen when license: autogen is CC-BY-4.0, LLFn is MIT; pick LLFn when license: LLFn is MIT, autogen is CC-BY-4.0.

Markdown twin · autogen alternatives · LLFn alternatives

GraphCanon updated today

autogen logo

autogen

microsoft/autogen

★ 60kpushed Apr 15, 2026
vs
LLFn logo

LLFn

orgexyz/LLFn

★ 96pushed Jul 30, 2023

Trust & integrity

SignalautogenLLFn
Maintenance
Steady (87d since push)
As of today · github_public_v1
Dormant (1076d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none
autogen trust reportLLFn trust reportTrust methodology

Tagline

autogen
A programming framework for agentic AI
LLFn
A light-weight framework for creating applications using LLMs

Stars

autogen
60k
LLFn
96

Forks

autogen
9.0k
LLFn
7

Open issues

autogen
945
LLFn
1

Language

autogen
Python
LLFn
Python

Adopt for

autogen
AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models.
LLFn
-

Persona

autogen
-
LLFn
-

Runtime

autogen
-
LLFn
-

License

autogen
CC-BY-4.0
LLFn
MIT

Last pushed

autogen
Apr 15, 2026
LLFn
Jul 30, 2023

Categories

autogen
AI Agents, LLM Frameworks
LLFn
LLM Frameworks

Trust and health

Maintenance

autogen
Steady (60%)
LLFn
Dormant (18%)

Days since push

autogen
87d
LLFn
1076d

Open issues (now)

autogen
945
LLFn
1

Full report

autogen
Trust report
LLFn
Trust report

Choose autogen if…

  • License: autogen is CC-BY-4.0, LLFn is MIT.
  • Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure..
  • Tags unique to autogen: llm-framework, autogen, agents, ai.
  • Also covers AI Agents.
  • You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.

When NOT to use autogen

  • If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework.
  • When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited.
  • You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities.
GitHubDetails

Choose LLFn if…

  • License: LLFn is MIT, autogen is CC-BY-4.0.
  • Tags unique to LLFn: python.
  • Leaner open-issue backlog (1).

When NOT to use LLFn

  • Last GitHub push was 1077 days ago (dormant maintenance, Jul 30, 2023). Validate activity before betting a new project on LLFn.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Explore

autogen trust report →LLFn trust report →AI Agents category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: autogen 60k · LLFn 96 (synced Jul 11, 2026).

Common questions

What is the difference between autogen and LLFn?
autogen: A programming framework for agentic AI. LLFn: A light-weight framework for creating applications using LLMs. See the comparison table for live GitHub stats and shared categories.
When should I choose autogen over LLFn?
Choose autogen over LLFn when License: autogen is CC-BY-4.0, LLFn is MIT; Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.; Tags unique to autogen: llm-framework, autogen, agents, ai; Also covers AI Agents; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.
When should I choose LLFn over autogen?
Choose LLFn over autogen when License: LLFn is MIT, autogen is CC-BY-4.0; Tags unique to LLFn: python; Leaner open-issue backlog (1).
When should I avoid autogen?
If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. You need solutions which do not involve additional installations for server components such as playwright/mcp, as AutoGen requires this setup for certain functionalities.
When should I avoid LLFn?
Last GitHub push was 1077 days ago (dormant maintenance, Jul 30, 2023). Validate activity before betting a new project on LLFn. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is autogen or LLFn more popular on GitHub?
autogen has more GitHub stars (59,658 vs 96). Stars measure visibility, not whether either tool fits your constraints.
Are autogen and LLFn open source?
Yes - both are open-source projects on GitHub (autogen: CC-BY-4.0, LLFn: MIT).
Where can I find alternatives to autogen or LLFn?
GraphCanon lists graph-backed alternatives at autogen alternatives and LLFn alternatives (autogen markdown twin, LLFn markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, autogen or LLFn?
autogen: Steady. LLFn: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for autogen and LLFn?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: autogen trust report; LLFn trust report.