GraphCanon
Home/Compare/nas-env vs AutoGPT

Comparison

nas-env vs AutoGPT

Verdict

Pick nas-env when license: nas-env is MIT, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, nas-env is MIT.

Markdown twin · nas-env alternatives · AutoGPT alternatives

GraphCanon updated today

nas-env logo

nas-env

gomerudo/nas-env

★ 31pushed May 4, 2020
vs
AutoGPT logo

AutoGPT

Significant-Gravitas/AutoGPT

★ 185kpushed Jul 11, 2026

Trust & integrity

Signalnas-envAutoGPT
Maintenance
Dormant (2259d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal 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
nas-env trust reportAutoGPT trust reportTrust methodology

Tagline

nas-env
A simple OpenAI Gym environment for Neural Architecture Search (NAS)
AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on.

Stars

nas-env
31
AutoGPT
185k

Forks

nas-env
3
AutoGPT
46k

Open issues

nas-env
0
AutoGPT
494

Language

nas-env
Python
AutoGPT
Python

Adopt for

nas-env
-
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

nas-env
-
AutoGPT
-

Runtime

nas-env
-
AutoGPT
-

License

nas-env
MIT
AutoGPT
Other

Last pushed

nas-env
May 4, 2020
AutoGPT
Jul 11, 2026

Categories

nas-env
LLM Frameworks
AutoGPT
AI Agents, LLM Frameworks

Trust and health

Maintenance

nas-env
Dormant (18%)
AutoGPT
Very active (96%)

Days since push

nas-env
2259d
AutoGPT
0d

Open issues (now)

nas-env
0
AutoGPT
494

Owner type

nas-env
User
AutoGPT
Organization

Full report

nas-env
Trust report
AutoGPT
Trust report

Choose nas-env if…

  • License: nas-env is MIT, AutoGPT is Other.
  • Tags unique to nas-env: neural-architecture-search, reinforcement-learning, python, openai-gym.
  • Leaner open-issue backlog (0).

When NOT to use nas-env

  • Last GitHub push was 2259 days ago (dormant maintenance, May 4, 2020). Validate activity before betting a new project on nas-env.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Choose AutoGPT if…

  • License: AutoGPT is Other, nas-env is MIT.
  • 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

nas-env trust report →AutoGPT trust report →LLM Frameworks 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: nas-env 31 · AutoGPT 185k (synced Jul 11, 2026).

Common questions

What is the difference between nas-env and AutoGPT?
nas-env: A simple OpenAI Gym environment for Neural Architecture Search (NAS). 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 nas-env over AutoGPT?
Choose nas-env over AutoGPT when License: nas-env is MIT, AutoGPT is Other; Tags unique to nas-env: neural-architecture-search, reinforcement-learning, python, openai-gym; Leaner open-issue backlog (0).
When should I choose AutoGPT over nas-env?
Choose AutoGPT over nas-env when License: AutoGPT is Other, nas-env is MIT; 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 nas-env?
Last GitHub push was 2259 days ago (dormant maintenance, May 4, 2020). Validate activity before betting a new project on nas-env. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
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 nas-env or AutoGPT more popular on GitHub?
AutoGPT has more GitHub stars (185,464 vs 31). Stars measure visibility, not whether either tool fits your constraints.
Are nas-env and AutoGPT open source?
Yes - both are open-source projects on GitHub (nas-env: MIT, AutoGPT: Other).
Where can I find alternatives to nas-env or AutoGPT?
GraphCanon lists graph-backed alternatives at nas-env alternatives and AutoGPT alternatives (nas-env 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, nas-env or AutoGPT?
nas-env: Dormant. 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 nas-env and AutoGPT?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: nas-env trust report; AutoGPT trust report.