Comparison
llm-course vs superagent
Verdict
Pick llm-course when license: llm-course is Apache-2.0, superagent is MIT; pick superagent when license: superagent is MIT, llm-course is Apache-2.0.
Markdown twin · llm-course alternatives · superagent alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | llm-course | superagent |
|---|---|---|
| Maintenance | Slowing (155d since push) As of today · github_public_v1 | Slowing (91d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- llm-course
- Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
- superagent
- Superagent protects your AI applications against prompt injections, data leaks, and harmful outputs. Embed safety directly into your app and prove compliance to your customers.
Stars
- llm-course
- 81k
- superagent
- 6.7k
Forks
- llm-course
- 9.4k
- superagent
- 963
Open issues
- llm-course
- 84
- superagent
- 9
Language
- llm-course
- -
- superagent
- TypeScript
Adopt for
- llm-course
- The llm-course provides a comprehensive guided course on Large Language Models (LLMs), divided into three parts: LLM Fundamentals, The LLM Scientist, and The LLM Engineer. It includes resources such as Colab notebooks to
- superagent
- -
Persona
- llm-course
- -
- superagent
- -
Runtime
- llm-course
- -
- superagent
- -
License
- llm-course
- Apache-2.0
- superagent
- MIT
Last pushed
- llm-course
- Feb 5, 2026
- superagent
- Apr 11, 2026
Categories
- llm-course
- Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
- superagent
- AI Agents, Inference & Serving, LLM Frameworks
Trust and health
Days since push
- llm-course
- 155d
- superagent
- 91d
Open issues (now)
- llm-course
- 84
- superagent
- 9
Owner type
- llm-course
- User
- superagent
- Organization
Full report
- llm-course
- Trust report
- superagent
- Trust report
Shared compatibility
- Python · llm-course: Python runtime · superagent: Python runtime
Choose llm-course if…
- License: llm-course is Apache-2.0, superagent is MIT.
- Requirements: Course materials are available in Colab notebooks; access requires a Google account.
- Tags unique to llm-course: colab-notebooks, course, large-language-models, machine-learning.
- Also covers Evaluation & Observability, Model Training.
- - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge
When NOT to use llm-course
- - If you only require a quick introduction to LLMs without deep dive into core components
- - When you prefer working directly with commercial platforms that provide complete services rather than following detailed steps on building and deploying models yourself through this course's open,DI
Choose superagent if…
- License: superagent is MIT, llm-course is Apache-2.0.
- Tags unique to superagent: ai, anthropic, guardrails, llm.
- Also covers AI Agents.
When NOT to use superagent
- Last GitHub push was 92 days ago (slowing maintenance, Apr 11, 2026). Validate activity before betting a new project on superagent.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
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 Jul 11, 2026
- GitHub forks (mlabonne/llm-course) · observed Jul 11, 2026
- Last push (mlabonne/llm-course) · observed Feb 5, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (superagent-ai/superagent) · observed Jul 11, 2026
- GitHub forks (superagent-ai/superagent) · observed Jul 11, 2026
- Last push (superagent-ai/superagent) · observed Apr 11, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: llm-course 81k · superagent 6.7k (synced Jul 11, 2026).
Common questions
- What is the difference between llm-course and superagent?
- llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.. superagent: Superagent protects your AI applications against prompt injections, data leaks, and harmful outputs. Embed safety directly into your app and prove compliance to your customers.. See the comparison table for live GitHub stats and shared categories.
- When should I choose llm-course over superagent?
- Choose llm-course over superagent when License: llm-course is Apache-2.0, superagent is MIT; Requirements: Course materials are available in Colab notebooks; access requires a Google account; Tags unique to llm-course: colab-notebooks, course, large-language-models, machine-learning; Also covers Evaluation & Observability, Model Training; - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge.
- When should I choose superagent over llm-course?
- Choose superagent over llm-course when License: superagent is MIT, llm-course is Apache-2.0; Tags unique to superagent: ai, anthropic, guardrails, llm; Also covers AI Agents.
- When should I avoid llm-course?
- - If you only require a quick introduction to LLMs without deep dive into core components - When you prefer working directly with commercial platforms that provide complete services rather than following detailed steps on building and deploying models yourself through this course's open,DI
- When should I avoid superagent?
- Last GitHub push was 92 days ago (slowing maintenance, Apr 11, 2026). Validate activity before betting a new project on superagent. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Is llm-course or superagent more popular on GitHub?
- llm-course has more GitHub stars (80,839 vs 6,669). Stars measure visibility, not whether either tool fits your constraints.
- Are llm-course and superagent open source?
- Yes - both are open-source projects on GitHub (llm-course: Apache-2.0, superagent: MIT).
- Where can I find alternatives to llm-course or superagent?
- GraphCanon lists graph-backed alternatives at llm-course alternatives and superagent alternatives (llm-course markdown twin, superagent 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 superagent?
- llm-course: Slowing. superagent: 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 llm-course and superagent?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm-course trust report; superagent trust report.