--- title: "Reading_groups vs awesome-LLM-resources" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/crazyofapple-reading-groups-vs-wangrongsheng-awesome-llm-resources" tools: ["crazyofapple-reading-groups", "wangrongsheng-awesome-llm-resources"] --- # Reading_groups vs awesome-LLM-resources *GraphCanon updated Oct 11, 2026* ## Verdict Pick Reading_groups if 用于跟踪、整理和学习大规模语言模型相关的文章、课程材料和实验演示，适用于希望了解最新技术进展、优化策略、应用案例以及深度分析的研究者。; pick awesome-LLM-resources if awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference. [Reading_groups](https://github.com/crazyofapple/Reading_groups) reports 204 GitHub stars, 7 forks, and 0 open issues, last pushed Aug 8, 2023. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) has 9.0k stars, 993 forks, and 40 open issues, last pushed Sep 14, 2026. Figures are from public GitHub metadata via [Reading_groups's repository](https://github.com/crazyofapple/Reading_groups) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources). | | [Reading_groups](/tools/crazyofapple-reading-groups.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Tagline | 资源整理和追踪大规模预训练语言模型相关文章 | Summary of the world's best LLM resources. | | Stars | 204 | 8,968 | | Forks | 7 | 993 | | Open issues | 0 | 40 | | Language | - | - | | Adopt for | 用于跟踪、整理和学习大规模语言模型相关的文章、课程材料和实验演示，适用于希望了解最新技术进展、优化策略、应用案例以及深度分析的研究者。 | awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference. | | Persona | - | - | | Runtime | - | - | | License | - | The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution. | | Categories | Developer Tools, Evaluation & Observability, LLM Frameworks, Model Training | AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Reading_groups](/tools/crazyofapple-reading-groups.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1159d | 3d | | Open issues (now) | 0 | 40 | | Stars delta | +1 (30d) | +123 (30d) | | Open issues delta | 0 (30d) | +17 (30d) | | Full report | [trust report](/tools/crazyofapple-reading-groups/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) | ## Shared compatibility - **ChatGPT**: [Reading_groups](/tools/crazyofapple-reading-groups.md) - Works with ChatGPT; [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) - Works with ChatGPT ## Decision facts: Reading_groups - **Adopt for:** 用于跟踪、整理和学习大规模语言模型相关的文章、课程材料和实验演示，适用于希望了解最新技术进展、优化策略、应用案例以及深度分析的研究者。 ## Decision facts: awesome-LLM-resources - **Pricing:** freemium - The repository itself is free to use, but some linked resources may require payment or have associated costs. - **Requirements:** The repository does not specify any technical requirements for accessing its content. - **Adopt for:** awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference. - **License detail:** The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution. ## Choose when ### Choose Reading_groups if… - Tags unique to Reading_groups: chatgpt, gpt-3, gpt-4, llms. - 您想深入理解特定的大规模预训练语言模型（如GPT-4）、其性能测试及其局限性时 - Leaner open-issue backlog (0). ### Choose awesome-LLM-resources if… - Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs.. - Requirements: The repository does not specify any technical requirements for accessing its content.. - Tags unique to awesome-LLM-resources: awesome-list, book, course, llama. - Also covers AI Agents, Computer Vision, Data & Retrieval, Inference & Serving. - When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more. ## When NOT to use Reading_groups - 。Reading_groups， - NLP， ## When NOT to use awesome-LLM-resources - If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider. - When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support. ## Common questions ### What is the difference between Reading_groups and awesome-LLM-resources? Reading_groups: 资源整理和追踪大规模预训练语言模型相关文章. 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 Reading_groups over awesome-LLM-resources? Choose Reading_groups over awesome-LLM-resources when Tags unique to Reading_groups: chatgpt, gpt-3, gpt-4, llms; 您想深入理解特定的大规模预训练语言模型（如GPT-4）、其性能测试及其局限性时; Leaner open-issue backlog (0). ### When should I choose awesome-LLM-resources over Reading_groups? Choose awesome-LLM-resources over Reading_groups when Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs.; Requirements: The repository does not specify any technical requirements for accessing its content.; Tags unique to awesome-LLM-resources: awesome-list, book, course, llama; Also covers AI Agents, Computer Vision, Data & Retrieval, Inference & Serving; When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more. ### When should I avoid Reading_groups? 。Reading_groups， NLP， ### When should I avoid awesome-LLM-resources? If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider. When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support. ### Is Reading_groups or awesome-LLM-resources more popular on GitHub? awesome-LLM-resources has more GitHub stars (8,968 vs 204). Stars measure visibility, not whether either tool fits your constraints. ### Are Reading_groups and awesome-LLM-resources open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Reading_groups or awesome-LLM-resources? GraphCanon lists graph-backed alternatives at [Reading_groups alternatives](/tools/crazyofapple-reading-groups/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([Reading_groups markdown twin](/tools/crazyofapple-reading-groups/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/crazyofapple-reading-groups-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, Reading_groups or awesome-LLM-resources? Reading_groups: 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 Reading_groups and awesome-LLM-resources? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Reading_groups trust report](/tools/crazyofapple-reading-groups/trust); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=crazyofapple-reading-groups`](/api/graphcanon/graph?tool=crazyofapple-reading-groups) - 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/_