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Comparison

LaVague vs autogen

Verdict

Pick LaVague if large Action Model (LaVague) framework supports developing AI web agents using customizable Large Language Models (LLMs), offering tracking of token usage for cost estimation purposes; pick autogen if autoGen is a Python-based framework for developing agentic AI systems, offering tools for integrating with external models and services, and a no-code GUI for easier interaction.

Markdown twin · LaVague alternatives · autogen alternatives

GraphCanon updated Sep 20, 2026

12views this month

LaVague logo

LaVague

lavague-ai/LaVague

★ 6.4kpushed Jan 21, 2025
vs
autogen logo

autogen

microsoft/autogen

★ 61kpushed Apr 15, 2026

Trust & integrity

SignalLaVagueautogen
Maintenance
Dormant (574d since push)
As of Aug 18, 2026 · github_public_v1
Slowing (155d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Aug 18, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Sep 18, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1
LaVague trust reportautogen trust reportTrust methodology

Tagline

LaVague
Large Action Model framework to develop AI Web Agents
autogen
A programming framework for agentic AI

Stars

LaVague
6.4k
autogen
61k

Forks

LaVague
573
autogen
9.2k

Open issues

LaVague
104
autogen
1.1k

Language

LaVague
Python
autogen
Python

Adopt for

LaVague
Large Action Model (LaVague) framework supports developing AI web agents using customizable Large Language Models (LLMs), offering tracking of token usage for cost estimation purposes.
autogen
AutoGen is a Python-based framework for developing agentic AI systems, offering tools for integrating with external models and services, and a no-code GUI for easier interaction.

Persona

LaVague
-
autogen
-

Runtime

LaVague
-
autogen
-

License

LaVague
LaVague's license (Apache-2.0) allows free use in both open and closed-source applications, provided that copyright notices are preserved.
autogen
CC-BY-4.0

Last pushed

LaVague
Jan 21, 2025
autogen
Apr 15, 2026

Categories

LaVague
AI Agents
autogen
AI Agents, LLM Frameworks

Trust and health

Maintenance

LaVague
Dormant (18%)
autogen
Slowing (36%)

Days since push

LaVague
574d
autogen
155d

Open issues (now)

LaVague
104
autogen
1.1k

Stars delta

LaVague
+6 (30d)
autogen
+897 (30d)

Open issues delta

LaVague
0 (30d)
autogen
+105 (30d)

Full report

LaVague
Trust report
autogen
Trust report

Choose LaVague if…

  • License: LaVague is Apache-2.0, autogen is CC-BY-4.0.
  • Pricing: Free to use with customizable LLMs; actual costs depend on the specific LLM used and operational complexity..
  • Requirements: Min 2 GB RAM; Requires Python for development..
  • Tags unique to LaVague: browser, large-action-model, llm, oss.
  • When you need a flexible framework that allows customization of LLMs, particularly if your primary model is OpenAI's `gpt4-o` or similar models.

When NOT to use LaVague

  • Avoid using LaVague if you are working on projects that do not involve AI web agent development, as the framework is specifically designed around this use-case.
  • Do not opt for LaVague if you require a non-Python environment for your development since the framework is Python-based.
GitHubDetails

Choose autogen if…

  • License: autogen is CC-BY-4.0, LaVague is Apache-2.0.
  • Requirements: AutoGen requires Python 3.10 or later.; Installation of AutoGen Studio is optional for no-code GUI interaction.; Ensure trusted MCP servers are used to avoid security risks..
  • Tags unique to autogen: agentic, agentic-agi, agents, autogen.
  • Also covers LLM Frameworks.
  • When you need a structured approach to create and manage AI agents with Python.

When NOT to use autogen

  • If your project requires a version of Python earlier than 3.10, as AutoGen is not compatible.
  • When you need a framework that does not rely on potentially untrusted MCP servers for execution.
  • If your project does not require or benefit from the no-code GUI provided by AutoGen Studio.
  • When you prefer a framework that does not involve the complexity of setting up and managing multiple MCP servers.
GitHubDetails

Explore

LaVague trust report →autogen 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: LaVague 6.4k · autogen 61k (synced Sep 20, 2026).

Common questions

What is the difference between LaVague and autogen?
LaVague: Large Action Model framework to develop AI Web Agents. autogen: A programming framework for agentic AI. See the comparison table for live GitHub stats and shared categories.
When should I choose LaVague over autogen?
Choose LaVague over autogen when License: LaVague is Apache-2.0, autogen is CC-BY-4.0; Pricing: Free to use with customizable LLMs; actual costs depend on the specific LLM used and operational complexity.; Requirements: Min 2 GB RAM; Requires Python for development.; Tags unique to LaVague: browser, large-action-model, llm, oss; When you need a flexible framework that allows customization of LLMs, particularly if your primary model is OpenAI's gpt4-o or similar models.
When should I choose autogen over LaVague?
Choose autogen over LaVague when License: autogen is CC-BY-4.0, LaVague is Apache-2.0; Requirements: AutoGen requires Python 3.10 or later.; Installation of AutoGen Studio is optional for no-code GUI interaction.; Ensure trusted MCP servers are used to avoid security risks.; Tags unique to autogen: agentic, agentic-agi, agents, autogen; Also covers LLM Frameworks; When you need a structured approach to create and manage AI agents with Python.
When should I avoid LaVague?
Avoid using LaVague if you are working on projects that do not involve AI web agent development, as the framework is specifically designed around this use-case. Do not opt for LaVague if you require a non-Python environment for your development since the framework is Python-based.
When should I avoid autogen?
If your project requires a version of Python earlier than 3.10, as AutoGen is not compatible. When you need a framework that does not rely on potentially untrusted MCP servers for execution. If your project does not require or benefit from the no-code GUI provided by AutoGen Studio. When you prefer a framework that does not involve the complexity of setting up and managing multiple MCP servers.
Is LaVague or autogen more popular on GitHub?
autogen has more GitHub stars (61,036 vs 6,386). Stars measure visibility, not whether either tool fits your constraints.
Are LaVague and autogen open source?
Yes - both are open-source projects on GitHub (LaVague: Apache-2.0, autogen: CC-BY-4.0).
Where can I find alternatives to LaVague or autogen?
GraphCanon lists graph-backed alternatives at LaVague alternatives and autogen alternatives (LaVague markdown twin, autogen 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, LaVague or autogen?
LaVague: Dormant. autogen: Slowing. 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 LaVague and autogen?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LaVague trust report; autogen trust report.

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