Home/Compare/holaOS vs AutoGPT

Comparison

holaOS vs AutoGPT

Verdict

Pick holaOS when holaOS is primarily TypeScript; AutoGPT is Python; pick AutoGPT when autoGPT is primarily Python; holaOS is TypeScript.

Markdown twin · holaOS alternatives · AutoGPT alternatives

GraphCanon updated today

holaOS logo

holaOS

holaboss-ai/holaOS

5.5kpushed Jun 22, 2026
vs
AutoGPT logo

AutoGPT

Significant-Gravitas/AutoGPT

185kpushed Jul 11, 2026

Trust & integrity

SignalholaOSAutoGPT
Maintenance
Active (19d since push)
As of today · github_public_v1
Very active (0d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of 1d · github_public_v1
Security (OSV)
No MCP manifest
As of today · mcp_manifest
No lockfile
As of 1d · none

Tagline

holaOS
Your super agent for work: local-first, learn your working context in mins and never forget it.
AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on.

Stars

holaOS
5.5k
AutoGPT
185k

Forks

holaOS
392
AutoGPT
46k

Open issues

holaOS
7
AutoGPT
494

Language

holaOS
TypeScript
AutoGPT
Python

Adopt for

holaOS
-
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

holaOS
-
AutoGPT
-

Runtime

holaOS
-
AutoGPT
-

License

holaOS
Other
AutoGPT
Other

Last pushed

holaOS
Jun 22, 2026
AutoGPT
Jul 11, 2026

Categories

holaOS
AI Agents, Inference & Serving, LLM Frameworks
AutoGPT
AI Agents, LLM Frameworks

Trust and health

Maintenance

holaOS
Active (82%)
AutoGPT
Very active (96%)

Days since push

holaOS
19d
AutoGPT
0d

Open issues (now)

holaOS
7
AutoGPT
494

Security scan

holaOS
No MCP manifest
AutoGPT
No lockfile

Full report

Choose holaOS if…

  • holaOS is primarily TypeScript; AutoGPT is Python.
  • Tags unique to holaOS: agent, agent-harness, agent-os, agentic.
  • Also covers Inference & Serving.

When NOT to use holaOS

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose AutoGPT if…

  • AutoGPT is primarily Python; holaOS is TypeScript.
  • Tags unique to AutoGPT: agentic-ai, agents, autonomous-agents, claude.
  • 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.

Explore

Sources

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

GitHub stars on cards: holaOS 5.5k · AutoGPT 185k (synced Jul 11, 2026).

Common questions

What is the difference between holaOS and AutoGPT?
holaOS: Your super agent for work: local-first, learn your working context in mins and never forget it.. 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 holaOS over AutoGPT?
Choose holaOS over AutoGPT when holaOS is primarily TypeScript; AutoGPT is Python; Tags unique to holaOS: agent, agent-harness, agent-os, agentic; Also covers Inference & Serving.
When should I choose AutoGPT over holaOS?
Choose AutoGPT over holaOS when AutoGPT is primarily Python; holaOS is TypeScript; Tags unique to AutoGPT: agentic-ai, agents, autonomous-agents, claude; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
When should I avoid holaOS?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. 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 holaOS or AutoGPT more popular on GitHub?
AutoGPT has more GitHub stars (185,464 vs 5,499). Stars measure visibility, not whether either tool fits your constraints.
Are holaOS and AutoGPT open source?
Yes - both are open-source projects on GitHub (holaOS: Other, AutoGPT: Other).
Where can I find alternatives to holaOS or AutoGPT?
GraphCanon lists graph-backed alternatives at holaOS alternatives and AutoGPT alternatives (holaOS 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, holaOS or AutoGPT?
holaOS: 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 holaOS and AutoGPT?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: holaOS trust report; AutoGPT trust report.