Home/Compare/llama-hub vs awesome-LLM-resources

Comparison

llama-hub vs awesome-LLM-resources

Verdict

Pick llama-hub if community-driven data loaders for LlamaIndex/LangChain; pick awesome-LLM-resources if awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.

Markdown twin · llama-hub alternatives · awesome-LLM-resources alternatives

GraphCanon updated Sep 20, 2026

7views this month

llama-hub logo

llama-hub

run-llama/llama-hub

★ 3.5kpushed Mar 1, 2024
vs
awesome-LLM-resources logo

awesome-LLM-resources

WangRongsheng/awesome-LLM-resources

★ 9.0kpushed Sep 14, 2026

Trust & integrity

Signalllama-hubawesome-LLM-resources
Maintenance
Archived (920d since push)
As of Sep 8, 2026 · github_public_v1
Very active (3d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 8, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
Published findings
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

Tagline

llama-hub
A library of data loaders for LLMs made by the community
awesome-LLM-resources
Summary of the world's best LLM resources.

Stars

llama-hub
3.5k
awesome-LLM-resources
9.0k

Forks

llama-hub
721
awesome-LLM-resources
993

Open issues

llama-hub
96
awesome-LLM-resources
40

Language

llama-hub
Jupyter Notebook
awesome-LLM-resources
-

Adopt for

llama-hub
community-driven data loaders for LlamaIndex/LangChain
awesome-LLM-resources
awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.

Persona

llama-hub
-
awesome-LLM-resources
-

Runtime

llama-hub
-
awesome-LLM-resources
-

License

llama-hub
MIT
awesome-LLM-resources
The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution.

Last pushed

llama-hub
Mar 1, 2024
awesome-LLM-resources
Sep 14, 2026

Categories

llama-hub
Data & Retrieval, Model Training
awesome-LLM-resources
AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training

Trust and health

Maintenance

llama-hub
Archived (8%)
awesome-LLM-resources
Very active (96%)

Days since push

llama-hub
920d
awesome-LLM-resources
3d

Archived on GitHub

llama-hub
Yes
awesome-LLM-resources
No

Open issues (now)

llama-hub
96
awesome-LLM-resources
40

Stars delta

llama-hub
-8 (30d)
awesome-LLM-resources
+123 (30d)

Open issues delta

llama-hub
0 (30d)
awesome-LLM-resources
+17 (30d)

Owner type

llama-hub
Organization
awesome-LLM-resources
User

OSV dependency advisories

llama-hub
Published findings
awesome-LLM-resources
No lockfile (source not queried)

Full report

llama-hub
Trust report
awesome-LLM-resources
Trust report

Choose llama-hub if…

  • License: llama-hub is MIT, awesome-LLM-resources is Apache-2.0.
  • Tags unique to llama-hub: community-driven, jupyter-notebook, langchain, llamaindex.
  • Community-specific features require engagement with community

When NOT to use llama-hub

  • Limited support if the community lacks activity
  • Not suitable without familiarity with Poetry for dependency management

Choose awesome-LLM-resources if…

  • License: awesome-LLM-resources is Apache-2.0, llama-hub is MIT.
  • Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs..
  • Requirements: The repository does not specify any technical requirements for accessing its content..
  • Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models.
  • Also covers AI Agents, Computer Vision, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks.
  • When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.

When NOT to use awesome-LLM-resources

  • If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider.
  • When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.

Explore

Sources

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

GitHub stars on cards: llama-hub 3.5k · awesome-LLM-resources 9.0k (synced Sep 20, 2026).

Common questions

What is the difference between llama-hub and awesome-LLM-resources?
llama-hub: A library of data loaders for LLMs made by the community. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories.
When should I choose llama-hub over awesome-LLM-resources?
Choose llama-hub over awesome-LLM-resources when License: llama-hub is MIT, awesome-LLM-resources is Apache-2.0; Tags unique to llama-hub: community-driven, jupyter-notebook, langchain, llamaindex; Community-specific features require engagement with community.
When should I choose awesome-LLM-resources over llama-hub?
Choose awesome-LLM-resources over llama-hub when License: awesome-LLM-resources is Apache-2.0, llama-hub is MIT; Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs.; Requirements: The repository does not specify any technical requirements for accessing its content.; Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models; Also covers AI Agents, Computer Vision, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks; When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.
When should I avoid llama-hub?
Limited support if the community lacks activity Not suitable without familiarity with Poetry for dependency management
When should I avoid awesome-LLM-resources?
If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider. When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.
Is llama-hub or awesome-LLM-resources more popular on GitHub?
awesome-LLM-resources has more GitHub stars (8,968 vs 3,461). Stars measure visibility, not whether either tool fits your constraints.
Are llama-hub and awesome-LLM-resources open source?
Yes - both are open-source projects on GitHub (llama-hub: MIT, awesome-LLM-resources: Apache-2.0).
Where can I find alternatives to llama-hub or awesome-LLM-resources?
GraphCanon lists graph-backed alternatives at llama-hub alternatives and awesome-LLM-resources alternatives (llama-hub markdown twin, awesome-LLM-resources 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 awesome-LLM-resources?
llama-hub: Archived. awesome-LLM-resources: 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 awesome-LLM-resources?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llama-hub trust report; awesome-LLM-resources trust report.

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