Comparison
DecryptPrompt vs llm-course
Verdict
Pick DecryptPrompt if decryptPrompt is an open-source repository that summarizes prompt and large language model research papers while offering related datasets and models for AI content generation facilitation; pick llm-course if llm-course provides a comprehensive curriculum on Large Language Models, including fundamental knowledge, building and deploying LLMs, and hands-on Colab notebooks.
Markdown twin · DecryptPrompt alternatives · llm-course alternatives
GraphCanon updated Sep 20, 2026
5views this month
Trust & integrity
| Signal | DecryptPrompt | llm-course |
|---|---|---|
| Maintenance | Active (12d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (224d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- DecryptPrompt
- Summarizes Prompt&LLM Papers, Open-source Data&Models, AIGC Applications
- llm-course
- Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Stars
- DecryptPrompt
- 3.4k
- llm-course
- 83k
Forks
- DecryptPrompt
- 318
- llm-course
- 9.7k
Open issues
- DecryptPrompt
- 0
- llm-course
- 90
Language
- DecryptPrompt
- -
- llm-course
- -
Adopt for
- DecryptPrompt
- DecryptPrompt is an open-source repository that summarizes prompt and large language model research papers while offering related datasets and models for AI content generation facilitation.
- llm-course
- llm-course provides a comprehensive curriculum on Large Language Models, including fundamental knowledge, building and deploying LLMs, and hands-on Colab notebooks.
Persona
- DecryptPrompt
- -
- llm-course
- -
Runtime
- DecryptPrompt
- -
- llm-course
- -
License
- DecryptPrompt
- -
- llm-course
- Apache-2.0
Last pushed
- DecryptPrompt
- Sep 8, 2026
- llm-course
- Feb 5, 2026
Categories
- DecryptPrompt
- Developer Tools, Model Training
- llm-course
- Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- DecryptPrompt
- Active (82%)
- llm-course
- Slowing (36%)
Days since push
- DecryptPrompt
- 12d
- llm-course
- 224d
Open issues (now)
- DecryptPrompt
- 0
- llm-course
- 90
Stars delta
- DecryptPrompt
- +13 (30d)
- llm-course
- +1.5k (30d)
Open issues delta
- DecryptPrompt
- -1 (30d)
- llm-course
- +4 (30d)
Full report
- DecryptPrompt
- Trust report
- llm-course
- Trust report
Choose DecryptPrompt if…
- Tags unique to DecryptPrompt: aigc, chain-of-thought, chatgpt, demonstration.
- When you need detailed summaries of prompt-engineering and LLM-related research, as DecryptPrompt is dedicated to this area.
- More recently updated (last pushed Sep 8, 2026).
When NOT to use DecryptPrompt
- Avoid using DecryptPrompt if you require a solution that supports languages other than English effectively, as the repository's descriptions are in Chinese.
- If your development needs go beyond summarization and data/model provision into complex coding examples or comprehensive API documentation, DecryptPrompt might not satisfy these requirements.
Choose llm-course if…
- Tags unique to llm-course: course, large-language-models, machine-learning, roadmap.
- Also covers Evaluation & Observability, Inference & Serving, LLM Frameworks.
- Use llm-course if you are looking for a structured learning path that includes both theoretical and practical aspects of LLMs, from fundamentals to deployment.
When NOT to use llm-course
- Avoid llm-course if you are seeking a course that focuses solely on theoretical aspects without practical implementation.
- Do not use llm-course if you prefer a more formal certification program or a course that is part of a university curriculum.
- Skip llm-course if you are looking for a tool that provides only code snippets or pre-built models without a structured learning path.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (DSXiangLi/DecryptPrompt) · observed Sep 20, 2026
- GitHub forks (DSXiangLi/DecryptPrompt) · observed Sep 20, 2026
- Last push (DSXiangLi/DecryptPrompt) · observed Sep 8, 2026
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (mlabonne/llm-course) · observed Sep 20, 2026
- GitHub forks (mlabonne/llm-course) · observed Sep 20, 2026
- Last push (mlabonne/llm-course) · observed Feb 5, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: DecryptPrompt 3.4k · llm-course 83k (synced Sep 20, 2026).
Common questions
- What is the difference between DecryptPrompt and llm-course?
- DecryptPrompt: Summarizes Prompt&LLM Papers, Open-source Data&Models, AIGC Applications. llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.. See the comparison table for live GitHub stats and shared categories.
- When should I choose DecryptPrompt over llm-course?
- Choose DecryptPrompt over llm-course when Tags unique to DecryptPrompt: aigc, chain-of-thought, chatgpt, demonstration; When you need detailed summaries of prompt-engineering and LLM-related research, as DecryptPrompt is dedicated to this area; More recently updated (last pushed Sep 8, 2026).
- When should I choose llm-course over DecryptPrompt?
- Choose llm-course over DecryptPrompt when Tags unique to llm-course: course, large-language-models, machine-learning, roadmap; Also covers Evaluation & Observability, Inference & Serving, LLM Frameworks; Use llm-course if you are looking for a structured learning path that includes both theoretical and practical aspects of LLMs, from fundamentals to deployment.
- When should I avoid DecryptPrompt?
- Avoid using DecryptPrompt if you require a solution that supports languages other than English effectively, as the repository's descriptions are in Chinese. If your development needs go beyond summarization and data/model provision into complex coding examples or comprehensive API documentation, DecryptPrompt might not satisfy these requirements.
- When should I avoid llm-course?
- Avoid llm-course if you are seeking a course that focuses solely on theoretical aspects without practical implementation. Do not use llm-course if you prefer a more formal certification program or a course that is part of a university curriculum. Skip llm-course if you are looking for a tool that provides only code snippets or pre-built models without a structured learning path.
- Is DecryptPrompt or llm-course more popular on GitHub?
- llm-course has more GitHub stars (83,011 vs 3,440). Stars measure visibility, not whether either tool fits your constraints.
- Are DecryptPrompt and llm-course open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to DecryptPrompt or llm-course?
- GraphCanon lists graph-backed alternatives at DecryptPrompt alternatives and llm-course alternatives (DecryptPrompt markdown twin, llm-course 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, DecryptPrompt or llm-course?
- DecryptPrompt: Active. llm-course: Slowing. 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 DecryptPrompt and llm-course?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DecryptPrompt trust report; llm-course trust report.