---
title: "chatgpt-plugin-eval vs llm-course"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/llm-platform-security-chatgpt-plugin-eval-vs-mlabonne-llm-course"
tools: ["llm-platform-security-chatgpt-plugin-eval", "mlabonne-llm-course"]
---

# chatgpt-plugin-eval vs llm-course

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick chatgpt-plugin-eval when tags unique to chatgpt-plugin-eval: chatgpt, chatgpt-plugins, llm, llm-platform; pick llm-course when requirements: Course materials are available in Colab notebooks; access requires a Google account.

[chatgpt-plugin-eval](https://llm-platform-security.github.io/chatgpt-plugin-eval/) reports 29 GitHub stars, 7 forks, and 1 open issues, last pushed Jul 29, 2024. [llm-course](https://mlabonne.github.io/blog/) has 81k stars, 9.4k forks, and 84 open issues, last pushed Feb 5, 2026. Figures are from public GitHub metadata via [chatgpt-plugin-eval's repository](https://github.com/llm-platform-security/chatgpt-plugin-eval) and [llm-course's repository](https://github.com/mlabonne/llm-course).

| | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | [llm-course](/tools/mlabonne-llm-course.md) |
| --- | --- | --- |
| Tagline | LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins | Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. |
| Stars | 29 | 80,839 |
| Forks | 7 | 9,421 |
| Open issues | 1 | 84 |
| Language | HTML | - |
| Adopt for | - | 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 |
| Persona | - | - |
| Runtime | - | - |
| License | - | Apache-2.0 |
| Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [chatgpt-plugin-eval](/tools/llm-platform-security-chatgpt-plugin-eval.md) | [llm-course](/tools/mlabonne-llm-course.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Slowing (36%) |
| Days since push | 712d | 155d |
| Open issues (now) | 1 | 84 |
| Owner type | Organization | User |
| Full report | [trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust.md) | [trust report](/tools/mlabonne-llm-course/trust.md) |

## Decision facts: llm-course

- **Requirements:** Course materials are available in Colab notebooks; access requires a Google account
- **Adopt for:** 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
- **License detail:** Apache-2.0

## Choose when

### Choose chatgpt-plugin-eval if…

- Tags unique to chatgpt-plugin-eval: chatgpt, chatgpt-plugins, llm, llm-platform.
- Leaner open-issue backlog (1).

### Choose llm-course if…

- 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 Model Training.
- - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge

## When NOT to use chatgpt-plugin-eval

- Last GitHub push was 712 days ago (dormant maintenance, Jul 29, 2024). Validate activity before betting a new project on chatgpt-plugin-eval.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- 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.

## 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

## Common questions

### What is the difference between chatgpt-plugin-eval and llm-course?

chatgpt-plugin-eval: LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins. 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 chatgpt-plugin-eval over llm-course?

Choose chatgpt-plugin-eval over llm-course when Tags unique to chatgpt-plugin-eval: chatgpt, chatgpt-plugins, llm, llm-platform; Leaner open-issue backlog (1).

### When should I choose llm-course over chatgpt-plugin-eval?

Choose llm-course over chatgpt-plugin-eval when 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 Model Training; - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge.

### When should I avoid chatgpt-plugin-eval?

Last GitHub push was 712 days ago (dormant maintenance, Jul 29, 2024). Validate activity before betting a new project on chatgpt-plugin-eval. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. 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.

### 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

### Is chatgpt-plugin-eval or llm-course more popular on GitHub?

llm-course has more GitHub stars (80,839 vs 29). Stars measure visibility, not whether either tool fits your constraints.

### Are chatgpt-plugin-eval and llm-course open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to chatgpt-plugin-eval or llm-course?

GraphCanon lists graph-backed alternatives at [chatgpt-plugin-eval alternatives](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives) and [llm-course alternatives](/tools/mlabonne-llm-course/alternatives) ([chatgpt-plugin-eval markdown twin](/tools/llm-platform-security-chatgpt-plugin-eval/alternatives.md), [llm-course markdown twin](/tools/mlabonne-llm-course/alternatives.md)), 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](/compare/llm-platform-security-chatgpt-plugin-eval-vs-mlabonne-llm-course.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, chatgpt-plugin-eval or llm-course?

chatgpt-plugin-eval: Dormant. 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 chatgpt-plugin-eval and llm-course?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [chatgpt-plugin-eval trust report](/tools/llm-platform-security-chatgpt-plugin-eval/trust); [llm-course trust report](/tools/mlabonne-llm-course/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=llm-platform-security-chatgpt-plugin-eval`](/api/graphcanon/graph?tool=llm-platform-security-chatgpt-plugin-eval)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_