--- title: "llm-books vs awesome-LLM-resources" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/morsoli-llm-books-vs-wangrongsheng-awesome-llm-resources" tools: ["morsoli-llm-books", "wangrongsheng-awesome-llm-resources"] --- # llm-books vs awesome-LLM-resources *GraphCanon updated Aug 21, 2026* ## Verdict Pick llm-books if decision-Critical Facts for 'llm-books'; pick awesome-LLM-resources if awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a. [llm-books](https://aitutor.liduos.com/) reports 767 GitHub stars, 53 forks, and 6 open issues, last pushed Nov 29, 2024. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) has 8.8k stars, 950 forks, and 23 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [llm-books's repository](https://github.com/morsoli/llm-books) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources). | | [llm-books](/tools/morsoli-llm-books.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Tagline | Notes on practical application development using LLM | Summary of the world's best LLM resources. | | Stars | 767 | 8,845 | | Forks | 53 | 950 | | Open issues | 6 | 23 | | Language | Python | - | | Adopt for | Decision-Critical Facts for 'llm-books' | awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a | | Persona | - | - | | Runtime | - | - | | License | Unknown License | Apache-2.0 | | Categories | Developer Tools, LLM Frameworks | AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm-books](/tools/morsoli-llm-books.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 629d | 2d | | Open issues (now) | 6 | 23 | | Stars delta | 0 (30d) | +142 (30d) | | Open issues delta | 0 (30d) | -13 (30d) | | Full report | [trust report](/tools/morsoli-llm-books/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) | **Typed relationship:** llm-books _(integrates with)_ awesome-LLM-resources Could integrate as a resource providing practical book notes and guidance for building with LLMs mentioned in this repository. ## Decision facts: llm-books - **Pricing:** unknown - **Adopt for:** Decision-Critical Facts for 'llm-books' - **License detail:** Unknown License ## Decision facts: awesome-LLM-resources - **Adopt for:** awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a ## Choose when ### Choose llm-books if… - Could integrate as a resource providing practical book notes and guidance for building with LLMs mentioned in this repository. - Tags unique to llm-books: chatgpt, chatgpt-api, langchain, llmops. - llm-books ships Docker support for self-hosted deployment. - Decision-Critical Facts for 'llm-books' ### Choose awesome-LLM-resources if… - Could integrate as a resource providing practical book notes and guidance for building with LLMs mentioned in this repository. - Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models. - Also covers AI Agents, Evaluation & Observability, Inference & Serving, Model Training. - - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ## When NOT to use llm-books - Last GitHub push was 630 days ago (dormant maintenance, Nov 29, 2024). Validate activity before betting a new project on llm-books. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use awesome-LLM-resources - - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ## Common questions ### What is the difference between llm-books and awesome-LLM-resources? llm-books: Notes on practical application development using LLM. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm-books over awesome-LLM-resources? Choose llm-books over awesome-LLM-resources when Could integrate as a resource providing practical book notes and guidance for building with LLMs mentioned in this repository; Tags unique to llm-books: chatgpt, chatgpt-api, langchain, llmops; llm-books ships Docker support for self-hosted deployment; Decision-Critical Facts for 'llm-books'. ### When should I choose awesome-LLM-resources over llm-books? Choose awesome-LLM-resources over llm-books when Could integrate as a resource providing practical book notes and guidance for building with LLMs mentioned in this repository; Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers AI Agents, Evaluation & Observability, Inference & Serving, Model Training; - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ### When should I avoid llm-books? Last GitHub push was 630 days ago (dormant maintenance, Nov 29, 2024). Validate activity before betting a new project on llm-books. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid awesome-LLM-resources? - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ### Is llm-books or awesome-LLM-resources more popular on GitHub? awesome-LLM-resources has more GitHub stars (8,845 vs 767). Stars measure visibility, not whether either tool fits your constraints. ### Are llm-books and awesome-LLM-resources open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to llm-books or awesome-LLM-resources? GraphCanon lists graph-backed alternatives at [llm-books alternatives](/tools/morsoli-llm-books/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([llm-books markdown twin](/tools/morsoli-llm-books/alternatives.md), [awesome-LLM-resources markdown twin](/tools/wangrongsheng-awesome-llm-resources/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/morsoli-llm-books-vs-wangrongsheng-awesome-llm-resources.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm-books or awesome-LLM-resources? llm-books: Dormant. awesome-LLM-resources: Very active. 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-books and awesome-LLM-resources? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-books trust report](/tools/morsoli-llm-books/trust); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=morsoli-llm-books`](/api/graphcanon/graph?tool=morsoli-llm-books) - 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/_