Comparison
llama-hub vs AutoGPT
Verdict
Pick llama-hub when llama-hub is primarily Jupyter Notebook; AutoGPT is Python; pick AutoGPT when autoGPT is primarily Python; llama-hub is Jupyter Notebook.
Markdown twin · llama-hub alternatives · AutoGPT alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | llama-hub | AutoGPT |
|---|---|---|
| Maintenance | Archived (861d 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) | 121 low (121 low) As of today · osv@v1 | No lockfile As of today · none |
Tagline
- llama-hub
- A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
- AutoGPT
- AutoGPT is the vision of accessible AI for everyone, to use and to build on.
Stars
- llama-hub
- 3.5k
- AutoGPT
- 185k
Forks
- llama-hub
- 719
- AutoGPT
- 46k
Open issues
- llama-hub
- 96
- AutoGPT
- 494
Language
- llama-hub
- Jupyter Notebook
- AutoGPT
- Python
Adopt for
- llama-hub
- -
- 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
- llama-hub
- -
- AutoGPT
- -
Runtime
- llama-hub
- -
- AutoGPT
- -
License
- llama-hub
- MIT
- AutoGPT
- Other
Last pushed
- llama-hub
- Mar 1, 2024
- AutoGPT
- Jul 11, 2026
Categories
- llama-hub
- Data & Retrieval, LLM Frameworks, Evaluation & Observability
- AutoGPT
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- llama-hub
- Archived (8%)
- AutoGPT
- Very active (96%)
Days since push
- llama-hub
- 861d
- AutoGPT
- 0d
Archived on GitHub
- llama-hub
- Yes
- AutoGPT
- No
Open issues (now)
- llama-hub
- 96
- AutoGPT
- 494
Security scan
- llama-hub
- 121 low (121 low)
- AutoGPT
- No lockfile
Full report
- llama-hub
- Trust report
- AutoGPT
- Trust report
Choose llama-hub if…
- llama-hub is primarily Jupyter Notebook; AutoGPT is Python.
- License: llama-hub is MIT, AutoGPT is Other.
- Tags unique to llama-hub: jupyter notebook.
- Also covers Data & Retrieval, Evaluation & Observability.
When NOT to use llama-hub
- llama-hub is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Choose AutoGPT if…
- AutoGPT is primarily Python; llama-hub is Jupyter Notebook.
- License: AutoGPT is Other, llama-hub 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (run-llama/llama-hub) · observed Jul 11, 2026
- GitHub forks (run-llama/llama-hub) · observed Jul 11, 2026
- Last push (run-llama/llama-hub) · observed Mar 1, 2024
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Significant-Gravitas/AutoGPT) · observed Jul 11, 2026
- GitHub forks (Significant-Gravitas/AutoGPT) · observed Jul 11, 2026
- Last push (Significant-Gravitas/AutoGPT) · observed Jul 11, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: llama-hub 3.5k · AutoGPT 185k (synced Jul 11, 2026).
Common questions
- What is the difference between llama-hub and AutoGPT?
- llama-hub: A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain. 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 llama-hub over AutoGPT?
- Choose llama-hub over AutoGPT when llama-hub is primarily Jupyter Notebook; AutoGPT is Python; License: llama-hub is MIT, AutoGPT is Other; Tags unique to llama-hub: jupyter notebook; Also covers Data & Retrieval, Evaluation & Observability.
- When should I choose AutoGPT over llama-hub?
- Choose AutoGPT over llama-hub when AutoGPT is primarily Python; llama-hub is Jupyter Notebook; License: AutoGPT is Other, llama-hub 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 llama-hub?
- llama-hub is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- 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 llama-hub or AutoGPT more popular on GitHub?
- AutoGPT has more GitHub stars (185,464 vs 3,473). Stars measure visibility, not whether either tool fits your constraints.
- Are llama-hub and AutoGPT open source?
- Yes - both are open-source projects on GitHub (llama-hub: MIT, AutoGPT: Other).
- Where can I find alternatives to llama-hub or AutoGPT?
- GraphCanon lists graph-backed alternatives at llama-hub alternatives and AutoGPT alternatives (llama-hub 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, llama-hub or AutoGPT?
- llama-hub: Archived. 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 llama-hub and AutoGPT?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llama-hub trust report; AutoGPT trust report.