Comparison
tutor-gpt vs awesome-LLM-resources
Verdict
Pick tutor-gpt if tutor-gpt - AI tutor with Theory-of-Mind for personalized education; pick awesome-LLM-resources if awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a.
Markdown twin · tutor-gpt alternatives · awesome-LLM-resources alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | tutor-gpt | awesome-LLM-resources |
|---|---|---|
| Maintenance | Slowing (175d since push) As of 6d · github_public_v1 | Very active (2d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 6d · github_public_v1 | Not a fork · Personal account As of 4d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- tutor-gpt
- AI tutor powered by Theory-of-Mind reasoning
- awesome-LLM-resources
- Summary of the world's best LLM resources.
Stars
- tutor-gpt
- 921
- awesome-LLM-resources
- 8.8k
Forks
- tutor-gpt
- 99
- awesome-LLM-resources
- 950
Open issues
- tutor-gpt
- 4
- awesome-LLM-resources
- 23
Language
- tutor-gpt
- TypeScript
- awesome-LLM-resources
- -
Adopt for
- tutor-gpt
- tutor-gpt - AI tutor with Theory-of-Mind for personalized education
- awesome-LLM-resources
- awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a
Persona
- tutor-gpt
- -
- awesome-LLM-resources
- -
Runtime
- tutor-gpt
- -
- awesome-LLM-resources
- -
License
- tutor-gpt
- GPL-3.0
- awesome-LLM-resources
- Apache-2.0
Last pushed
- tutor-gpt
- Feb 20, 2026
- awesome-LLM-resources
- Aug 14, 2026
Categories
- tutor-gpt
- Evaluation & Observability, LLM Frameworks
- awesome-LLM-resources
- AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- tutor-gpt
- Slowing (36%)
- awesome-LLM-resources
- Very active (96%)
Days since push
- tutor-gpt
- 175d
- awesome-LLM-resources
- 2d
Open issues (now)
- tutor-gpt
- 4
- awesome-LLM-resources
- 23
Stars delta
- tutor-gpt
- +8 (30d)
- awesome-LLM-resources
- +142 (30d)
Open issues delta
- tutor-gpt
- 0 (30d)
- awesome-LLM-resources
- -13 (30d)
Owner type
- tutor-gpt
- Organization
- awesome-LLM-resources
- User
Full report
- tutor-gpt
- Trust report
- awesome-LLM-resources
- Trust report
Choose tutor-gpt if…
- License: tutor-gpt is GPL-3.0, awesome-LLM-resources is Apache-2.0.
- Tags unique to tutor-gpt: ai, education, hacktoberfest, literacy.
- tutor-gpt ships Docker support for self-hosted deployment.
- For creating an educational experience that adapts to the cognitive and emotional state of students
When NOT to use tutor-gpt
- If looking for a tool focused solely on content delivery without personalized reasoning capabilities
- Projects requiring closed-source or proprietary licensing, as tutor-gpt uses the GPL-3.0 open-source license
Choose awesome-LLM-resources if…
- License: awesome-LLM-resources is Apache-2.0, tutor-gpt is GPL-3.0.
- Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models.
- Also covers AI Agents, Developer Tools, Inference & Serving, Model Training.
- - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies.
When NOT to use awesome-LLM-resources
- - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage.
- - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (plastic-labs/tutor-gpt) · observed Aug 15, 2026
- GitHub forks (plastic-labs/tutor-gpt) · observed Aug 15, 2026
- Last push (plastic-labs/tutor-gpt) · observed Feb 20, 2026
- License file (GPL-3.0) · observed Aug 15, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (WangRongsheng/awesome-LLM-resources) · observed Aug 17, 2026
- GitHub forks (WangRongsheng/awesome-LLM-resources) · observed Aug 17, 2026
- Last push (WangRongsheng/awesome-LLM-resources) · observed Aug 14, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 10, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: tutor-gpt 921 · awesome-LLM-resources 8.8k (synced Aug 15, 2026).
Common questions
- What is the difference between tutor-gpt and awesome-LLM-resources?
- tutor-gpt: AI tutor powered by Theory-of-Mind reasoning. 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 tutor-gpt over awesome-LLM-resources?
- Choose tutor-gpt over awesome-LLM-resources when License: tutor-gpt is GPL-3.0, awesome-LLM-resources is Apache-2.0; Tags unique to tutor-gpt: ai, education, hacktoberfest, literacy; tutor-gpt ships Docker support for self-hosted deployment; For creating an educational experience that adapts to the cognitive and emotional state of students.
- When should I choose awesome-LLM-resources over tutor-gpt?
- Choose awesome-LLM-resources over tutor-gpt when License: awesome-LLM-resources is Apache-2.0, tutor-gpt is GPL-3.0; Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers AI Agents, Developer Tools, Inference & Serving, Model Training; - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies.
- When should I avoid tutor-gpt?
- If looking for a tool focused solely on content delivery without personalized reasoning capabilities Projects requiring closed-source or proprietary licensing, as tutor-gpt uses the GPL-3.0 open-source license
- When should I avoid awesome-LLM-resources?
- - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content.
- Is tutor-gpt or awesome-LLM-resources more popular on GitHub?
- awesome-LLM-resources has more GitHub stars (8,845 vs 921). Stars measure visibility, not whether either tool fits your constraints.
- Are tutor-gpt and awesome-LLM-resources open source?
- Yes - both are open-source projects on GitHub (tutor-gpt: GPL-3.0, awesome-LLM-resources: Apache-2.0).
- Where can I find alternatives to tutor-gpt or awesome-LLM-resources?
- GraphCanon lists graph-backed alternatives at tutor-gpt alternatives and awesome-LLM-resources alternatives (tutor-gpt 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, tutor-gpt or awesome-LLM-resources?
- tutor-gpt: Slowing. 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 tutor-gpt and awesome-LLM-resources?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: tutor-gpt trust report; awesome-LLM-resources trust report.