Comparison
LeanCopilot vs awesome-LLM-resources
Verdict
Pick LeanCopilot if a system that leverages large language models for theorem proving in the Lean environment; 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 · LeanCopilot alternatives · awesome-LLM-resources alternatives
GraphCanon updated 5d
vs
Trust & integrity
| Signal | LeanCopilot | awesome-LLM-resources |
|---|---|---|
| Maintenance | Active (9d since push) As of 4w · github_public_v1 | Very active (2d since push) As of 5d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4w · github_public_v1 | Not a fork · Personal account As of 5d · 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
- LeanCopilot
- LLMs as Copilots for Theorem Proving in Lean
- awesome-LLM-resources
- Summary of the world's best LLM resources.
Stars
- LeanCopilot
- 1.3k
- awesome-LLM-resources
- 8.8k
Forks
- LeanCopilot
- 126
- awesome-LLM-resources
- 950
Open issues
- LeanCopilot
- 5
- awesome-LLM-resources
- 23
Language
- LeanCopilot
- C++
- awesome-LLM-resources
- -
Adopt for
- LeanCopilot
- A system that leverages large language models for theorem proving in the Lean environment.
- 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
- LeanCopilot
- -
- awesome-LLM-resources
- -
Runtime
- LeanCopilot
- -
- awesome-LLM-resources
- -
License
- LeanCopilot
- MIT
- awesome-LLM-resources
- Apache-2.0
Last pushed
- LeanCopilot
- Jul 16, 2026
- awesome-LLM-resources
- Aug 14, 2026
Categories
- LeanCopilot
- AI Agents, LLM Frameworks
- awesome-LLM-resources
- AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- LeanCopilot
- Active (82%)
- awesome-LLM-resources
- Very active (96%)
Days since push
- LeanCopilot
- 9d
- awesome-LLM-resources
- 2d
Open issues (now)
- LeanCopilot
- 5
- awesome-LLM-resources
- 23
Stars delta
- LeanCopilot
- Unknown
- awesome-LLM-resources
- +142 (30d)
Open issues delta
- LeanCopilot
- Unknown
- awesome-LLM-resources
- -13 (30d)
Owner type
- LeanCopilot
- Organization
- awesome-LLM-resources
- User
Full report
- LeanCopilot
- Trust report
- awesome-LLM-resources
- Trust report
Choose LeanCopilot if…
- License: LeanCopilot is MIT, awesome-LLM-resources is Apache-2.0.
- Tags unique to LeanCopilot: formal-mathematics, lean, lean4, llm-inference.
- LeanCopilot ships Docker support for self-hosted deployment.
- Need support with formal proof development in Lean or Lean4 specifically
When NOT to use LeanCopilot
- Working exclusively in theorem provers other than Lean or Lean4
- Looking for general-purpose AI programming assistant beyond Lean's domain
Choose awesome-LLM-resources if…
- License: awesome-LLM-resources is Apache-2.0, LeanCopilot is MIT.
- Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models.
- Also covers Developer Tools, Evaluation & Observability, 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 (lean-dojo/LeanCopilot) · observed Jul 25, 2026
- GitHub forks (lean-dojo/LeanCopilot) · observed Jul 25, 2026
- Last push (lean-dojo/LeanCopilot) · observed Jul 16, 2026
- License file (MIT) · observed Jul 25, 2026
- Decision facts (enrichment) · observed Jul 17, 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: LeanCopilot 1.3k · awesome-LLM-resources 8.8k (synced Jul 25, 2026).
Common questions
- What is the difference between LeanCopilot and awesome-LLM-resources?
- LeanCopilot: LLMs as Copilots for Theorem Proving in Lean. 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 LeanCopilot over awesome-LLM-resources?
- Choose LeanCopilot over awesome-LLM-resources when License: LeanCopilot is MIT, awesome-LLM-resources is Apache-2.0; Tags unique to LeanCopilot: formal-mathematics, lean, lean4, llm-inference; LeanCopilot ships Docker support for self-hosted deployment; Need support with formal proof development in Lean or Lean4 specifically.
- When should I choose awesome-LLM-resources over LeanCopilot?
- Choose awesome-LLM-resources over LeanCopilot when License: awesome-LLM-resources is Apache-2.0, LeanCopilot is MIT; Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers Developer Tools, Evaluation & Observability, 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 LeanCopilot?
- Working exclusively in theorem provers other than Lean or Lean4 Looking for general-purpose AI programming assistant beyond Lean's domain
- 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 LeanCopilot or awesome-LLM-resources more popular on GitHub?
- awesome-LLM-resources has more GitHub stars (8,845 vs 1,303). Stars measure visibility, not whether either tool fits your constraints.
- Are LeanCopilot and awesome-LLM-resources open source?
- Yes - both are open-source projects on GitHub (LeanCopilot: MIT, awesome-LLM-resources: Apache-2.0).
- Where can I find alternatives to LeanCopilot or awesome-LLM-resources?
- GraphCanon lists graph-backed alternatives at LeanCopilot alternatives and awesome-LLM-resources alternatives (LeanCopilot 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, LeanCopilot or awesome-LLM-resources?
- LeanCopilot: Active. 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 LeanCopilot and awesome-LLM-resources?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LeanCopilot trust report; awesome-LLM-resources trust report.