Comparison
llm-course vs WizardLM
Verdict
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; pick WizardLM if wizardLM powers language models like WizardCoder and WizardMath to excel in complex instruction handling.
Markdown twin · llm-course alternatives · WizardLM alternatives
GraphCanon updated Oct 7, 2026
vs
Trust & integrity
| Signal | llm-course | WizardLM |
|---|---|---|
| Maintenance | Slowing (224d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (487d since push) As of Oct 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 | Not a fork · Personal account As of Oct 7, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- llm-course
- Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
- WizardLM
- Empowering Large Pre-Trained Language Models to Follow Complex Instructions
Stars
- llm-course
- 83k
- WizardLM
- 9.5k
Forks
- llm-course
- 9.7k
- WizardLM
- 744
Open issues
- llm-course
- 90
- WizardLM
- 169
Language
- llm-course
- -
- WizardLM
- Python
Adopt for
- llm-course
- llm-course provides a comprehensive curriculum on Large Language Models, including fundamental knowledge, building and deploying LLMs, and hands-on Colab notebooks.
- WizardLM
- WizardLM powers language models like WizardCoder and WizardMath to excel in complex instruction handling.
Persona
- llm-course
- -
- WizardLM
- -
Runtime
- llm-course
- -
- WizardLM
- -
License
- llm-course
- Apache-2.0
- WizardLM
- (unknown)
Last pushed
- llm-course
- Feb 5, 2026
- WizardLM
- Jun 7, 2025
Categories
- llm-course
- Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
- WizardLM
- LLM Frameworks, Model Training
Trust and health
Maintenance
- llm-course
- Slowing (36%)
- WizardLM
- Dormant (18%)
Days since push
- llm-course
- 224d
- WizardLM
- 487d
Open issues (now)
- llm-course
- 90
- WizardLM
- 169
Stars delta
- llm-course
- +1.5k (30d)
- WizardLM
- 0 (30d)
Open issues delta
- llm-course
- +4 (30d)
- WizardLM
- 0 (30d)
Full report
- llm-course
- Trust report
- WizardLM
- Trust report
Shared compatibility
- Python · llm-course: Python runtime · WizardLM: Python runtime
Choose llm-course if…
- Tags unique to llm-course: course, llm, machine-learning, roadmap.
- Also covers Developer Tools, Evaluation & Observability, Inference & Serving.
- 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.
Choose WizardLM if…
- Tags unique to WizardLM: instruction-following, wizardcoder, wizardmath.
- When advanced coding tasks need precise solutions, surpassing GPT-3.5-Turbo and Gemini Pro
When NOT to use WizardLM
- If real-time updates are needed beyond Nov 2023, as performance is based on past benchmarks
- When looking for broad language capabilities of GPT-4, which outperformance in some benchmarks
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (nlpxucan/WizardLM) · observed Oct 7, 2026
- GitHub forks (nlpxucan/WizardLM) · observed Oct 7, 2026
- Last push (nlpxucan/WizardLM) · observed Jun 7, 2025
- License file (unknown) · observed Oct 7, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: llm-course 83k · WizardLM 9.5k (synced Sep 20, 2026).
Common questions
- What is the difference between llm-course and WizardLM?
- llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.. WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions. See the comparison table for live GitHub stats and shared categories.
- When should I choose llm-course over WizardLM?
- Choose llm-course over WizardLM when Tags unique to llm-course: course, llm, machine-learning, roadmap; Also covers Developer Tools, Evaluation & Observability, Inference & Serving; 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 choose WizardLM over llm-course?
- Choose WizardLM over llm-course when Tags unique to WizardLM: instruction-following, wizardcoder, wizardmath; When advanced coding tasks need precise solutions, surpassing GPT-3.5-Turbo and Gemini Pro.
- 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.
- When should I avoid WizardLM?
- If real-time updates are needed beyond Nov 2023, as performance is based on past benchmarks When looking for broad language capabilities of GPT-4, which outperformance in some benchmarks
- Is llm-course or WizardLM more popular on GitHub?
- llm-course has more GitHub stars (83,011 vs 9,480). Stars measure visibility, not whether either tool fits your constraints.
- Are llm-course and WizardLM open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to llm-course or WizardLM?
- GraphCanon lists graph-backed alternatives at llm-course alternatives and WizardLM alternatives (llm-course markdown twin, WizardLM 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, llm-course or WizardLM?
- llm-course: Slowing. WizardLM: Dormant. 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 llm-course and WizardLM?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm-course trust report; WizardLM trust report.