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Comparison

FEDOT vs AutoGPT

Verdict

Pick FEDOT when license: FEDOT is BSD-3-Clause, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, FEDOT is BSD-3-Clause.

Markdown twin · FEDOT alternatives · AutoGPT alternatives

GraphCanon updated today

FEDOT logo

FEDOT

aimclub/FEDOT

★ 709pushed Jul 8, 2026
vs
AutoGPT logo

AutoGPT

Significant-Gravitas/AutoGPT

★ 185kpushed Jul 11, 2026

Trust & integrity

SignalFEDOTAutoGPT
Maintenance
Very active (3d since push)
As of today · github_public_v1
Very active (0d 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)
27 low (27 low)
As of today · osv@v1
No lockfile
As of today · none
FEDOT trust reportAutoGPT trust reportTrust methodology

Tagline

FEDOT
Automated modeling and machine learning framework FEDOT
AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on.

Stars

FEDOT
709
AutoGPT
185k

Forks

FEDOT
92
AutoGPT
46k

Open issues

FEDOT
83
AutoGPT
494

Language

FEDOT
Python
AutoGPT
Python

Adopt for

FEDOT
-
AutoGPT
AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude.

Persona

FEDOT
-
AutoGPT
-

Runtime

FEDOT
-
AutoGPT
-

License

FEDOT
BSD-3-Clause
AutoGPT
Other

Last pushed

FEDOT
Jul 8, 2026
AutoGPT
Jul 11, 2026

Categories

FEDOT
LLM Frameworks, Data & Retrieval, Computer Vision
AutoGPT
AI Agents, LLM Frameworks

Trust and health

Days since push

FEDOT
3d
AutoGPT
0d

Open issues (now)

FEDOT
83
AutoGPT
494

Security scan

FEDOT
27 low (27 low)
AutoGPT
No lockfile

Full report

FEDOT
Trust report
AutoGPT
Trust report

Choose FEDOT if…

  • License: FEDOT is BSD-3-Clause, AutoGPT is Other.
  • Tags unique to FEDOT: automl, evolutionary-algorithms, genetic-programming, machine-learning.
  • Also covers Data & Retrieval, Computer Vision.

When NOT to use FEDOT

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
GitHubDetails

Choose AutoGPT if…

  • License: AutoGPT is Other, FEDOT is BSD-3-Clause.
  • Tags unique to AutoGPT: agents, llm, ai, artificial-intelligence.
  • Also covers AI Agents.
  • When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.

When NOT to use AutoGPT

  • Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework.
  • If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools.
GitHubDetails

Explore

FEDOT trust report →AutoGPT trust report →LLM Frameworks category →Data & Retrieval category →Computer Vision category →AI Agents 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: FEDOT 709 · AutoGPT 185k (synced Jul 11, 2026).

Common questions

What is the difference between FEDOT and AutoGPT?
FEDOT: Automated modeling and machine learning framework FEDOT. AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. See the comparison table for live GitHub stats and shared categories.
When should I choose FEDOT over AutoGPT?
Choose FEDOT over AutoGPT when License: FEDOT is BSD-3-Clause, AutoGPT is Other; Tags unique to FEDOT: automl, evolutionary-algorithms, genetic-programming, machine-learning; Also covers Data & Retrieval, Computer Vision.
When should I choose AutoGPT over FEDOT?
Choose AutoGPT over FEDOT when License: AutoGPT is Other, FEDOT is BSD-3-Clause; Tags unique to AutoGPT: agents, llm, ai, artificial-intelligence; Also covers AI Agents; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
When should I avoid FEDOT?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
When should I avoid AutoGPT?
Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools.
Is FEDOT or AutoGPT more popular on GitHub?
AutoGPT has more GitHub stars (185,464 vs 709). Stars measure visibility, not whether either tool fits your constraints.
Are FEDOT and AutoGPT open source?
Yes - both are open-source projects on GitHub (FEDOT: BSD-3-Clause, AutoGPT: Other).
Where can I find alternatives to FEDOT or AutoGPT?
GraphCanon lists graph-backed alternatives at FEDOT alternatives and AutoGPT alternatives (FEDOT markdown twin, AutoGPT 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, FEDOT or AutoGPT?
FEDOT: Very active. AutoGPT: Very active. 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 FEDOT and AutoGPT?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FEDOT trust report; AutoGPT trust report.