--- title: "LLMBook-zh.github.io vs llm-course" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/llmbook-zh-llmbook-zh-github-io-vs-mlabonne-llm-course" tools: ["llmbook-zh-llmbook-zh-github-io", "mlabonne-llm-course"] --- # LLMBook-zh.github.io vs llm-course *GraphCanon updated Aug 17, 2026* ## Verdict Pick LLMBook-zh.github.io if lLMBook-zh.github.io is a comprehensive guide on Large Language Models (LLMs) written in Chinese, ideal for Chinese-speaking beginners seeking to understand LLMs deeply; pick llm-course if 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. [LLMBook-zh.github.io](https://llmbook-zh.github.io/) reports 4.5k GitHub stars, 346 forks, and 13 open issues, last pushed Sep 2, 2025. [llm-course](https://mlabonne.github.io/blog/) has 82k stars, 9.5k forks, and 86 open issues, last pushed Feb 5, 2026. Figures are from public GitHub metadata via [LLMBook-zh.github.io's repository](https://github.com/LLMBook-zh/LLMBook-zh.github.io) and [llm-course's repository](https://github.com/mlabonne/llm-course). | | [LLMBook-zh.github.io](/tools/llmbook-zh-llmbook-zh-github-io.md) | [llm-course](/tools/mlabonne-llm-course.md) | | --- | --- | --- | | Tagline | 《大语言模型》全面介绍大模型技术的知识，适合初学者作为参考 | Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. | | Stars | 4,539 | 81,512 | | Forks | 346 | 9,490 | | Open issues | 13 | 86 | | Language | Python | - | | Adopt for | LLMBook-zh.github.io is a comprehensive guide on Large Language Models (LLMs) written in Chinese, ideal for Chinese-speaking beginners seeking to understand LLMs deeply. | 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 | Developer Tools, LLM Frameworks, Model Training | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLMBook-zh.github.io](/tools/llmbook-zh-llmbook-zh-github-io.md) | [llm-course](/tools/mlabonne-llm-course.md) | | --- | --- | --- | | Days since push | 349d | 183d | | Open issues (now) | 13 | 86 | | Stars delta | +13 (30d) | +771 (30d) | | Open issues delta | 0 (30d) | +1 (30d) | | Full report | [trust report](/tools/llmbook-zh-llmbook-zh-github-io/trust.md) | [trust report](/tools/mlabonne-llm-course/trust.md) | **Typed relationship:** LLMBook-zh.github.io _(related)_ llm-course ## Decision facts: LLMBook-zh.github.io - **Adopt for:** LLMBook-zh.github.io is a comprehensive guide on Large Language Models (LLMs) written in Chinese, ideal for Chinese-speaking beginners seeking to understand LLMs deeply. ## 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 LLMBook-zh.github.io if… - Graph edge: LLMBook-zh.github.io is a typed related of llm-course - see the relationship row above. - Tags unique to LLMBook-zh.github.io: artificial-intelligence, deep-learning, deep-neural-networks, fine-tuning. - Also covers Developer Tools. - When looking for detailed explanations of LLM technologies written in Chinese ### Choose llm-course if… - Requirements: Course materials are available in Colab notebooks; access requires a Google account. - Graph edge: llm-course is a typed related of LLMBook-zh.github.io - see the relationship row above. - Tags unique to llm-course: colab-notebooks, course, machine-learning, roadmap. - Also covers Evaluation & Observability, Inference & Serving. - - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge ## When NOT to use LLMBook-zh.github.io - If your primary language is not Chinese and you seek immediate practical application - For advanced researchers preferring the latest, cutting-edge research without detailed foundational explanations ## 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 LLMBook-zh.github.io and llm-course? LLMBook-zh.github.io: 《大语言模型》全面介绍大模型技术的知识，适合初学者作为参考. 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 LLMBook-zh.github.io over llm-course? Choose LLMBook-zh.github.io over llm-course when Graph edge: LLMBook-zh.github.io is a typed related of llm-course - see the relationship row above; Tags unique to LLMBook-zh.github.io: artificial-intelligence, deep-learning, deep-neural-networks, fine-tuning; Also covers Developer Tools; When looking for detailed explanations of LLM technologies written in Chinese. ### When should I choose llm-course over LLMBook-zh.github.io? Choose llm-course over LLMBook-zh.github.io when Requirements: Course materials are available in Colab notebooks; access requires a Google account; Graph edge: llm-course is a typed related of LLMBook-zh.github.io - see the relationship row above; Tags unique to llm-course: colab-notebooks, course, machine-learning, roadmap; Also covers Evaluation & Observability, Inference & Serving; - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge. ### When should I avoid LLMBook-zh.github.io? If your primary language is not Chinese and you seek immediate practical application For advanced researchers preferring the latest, cutting-edge research without detailed foundational explanations ### 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 LLMBook-zh.github.io or llm-course more popular on GitHub? llm-course has more GitHub stars (81,512 vs 4,539). Stars measure visibility, not whether either tool fits your constraints. ### Are LLMBook-zh.github.io and llm-course open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to LLMBook-zh.github.io or llm-course? GraphCanon lists graph-backed alternatives at [LLMBook-zh.github.io alternatives](/tools/llmbook-zh-llmbook-zh-github-io/alternatives) and [llm-course alternatives](/tools/mlabonne-llm-course/alternatives) ([LLMBook-zh.github.io markdown twin](/tools/llmbook-zh-llmbook-zh-github-io/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/llmbook-zh-llmbook-zh-github-io-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, LLMBook-zh.github.io or llm-course? LLMBook-zh.github.io: Slowing. 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 LLMBook-zh.github.io and llm-course? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLMBook-zh.github.io trust report](/tools/llmbook-zh-llmbook-zh-github-io/trust); [llm-course trust report](/tools/mlabonne-llm-course/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=llmbook-zh-llmbook-zh-github-io`](/api/graphcanon/graph?tool=llmbook-zh-llmbook-zh-github-io) - 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/_