--- title: "Awesome-LLM-Reasoning vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/atfortes-awesome-llm-reasoning-vs-sindresorhus-awesome" tools: ["atfortes-awesome-llm-reasoning", "sindresorhus-awesome"] --- # Awesome-LLM-Reasoning vs awesome *GraphCanon updated Jul 12, 2026* ## Verdict Pick Awesome-LLM-Reasoning if awesome-LLM-Reasoning is a curated collection of papers and resources dedicated to enhancing the reasoning abilities of large language models (LLMs) and multimodal large language models (MLLMs). Specifically, it delves深入; pick awesome if a curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. [Awesome-LLM-Reasoning](https://github.com/atfortes/Awesome-LLM-Reasoning) reports 3.6k GitHub stars, 212 forks, and 27 open issues, last pushed Apr 20, 2026. [awesome](https://github.com/sindresorhus/awesome) has 484k stars, 36k forks, and 92 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [Awesome-LLM-Reasoning's repository](https://github.com/atfortes/Awesome-LLM-Reasoning) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [Awesome-LLM-Reasoning](/tools/atfortes-awesome-llm-reasoning.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓 | 😎 Awesome lists about all kinds of interesting topics | | Stars | 3,648 | 484,026 | | Forks | 212 | 35,799 | | Open issues | 27 | 92 | | Language | - | - | | Adopt for | Awesome-LLM-Reasoning is a curated collection of papers and resources dedicated to enhancing the reasoning abilities of large language models (LLMs) and multimodal large language models (MLLMs). Specifically, it delves深入 | A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. | | Persona | - | - | | Runtime | - | - | | License | MIT | CC0-1.0 | | Categories | LLM Frameworks | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Awesome-LLM-Reasoning](/tools/atfortes-awesome-llm-reasoning.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 82d | 11d | | Open issues (now) | 27 | 92 | | Full report | [trust report](/tools/atfortes-awesome-llm-reasoning/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Decision facts: Awesome-LLM-Reasoning - **Adopt for:** Awesome-LLM-Reasoning is a curated collection of papers and resources dedicated to enhancing the reasoning abilities of large language models (LLMs) and multimodal large language models (MLLMs). Specifically, it delves深入 ## Decision facts: awesome - **Adopt for:** A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. ## Choose when ### Choose Awesome-LLM-Reasoning if… - License: Awesome-LLM-Reasoning is MIT, awesome is CC0-1.0. - Tags unique to Awesome-LLM-Reasoning: chain-of-thought, chatgpt, cot, deepseek. - Also covers LLM Frameworks. - 你正在寻找关于如何解锁和增强大语言模型（LLMs）和多模态大型语言模型（MLLMs）推理能力的论文和资源时。例如，如果你对理解和测试这些模型的符号推理能力感兴趣，这一资源将非常有用。 ### Choose awesome if… - License: awesome is CC0-1.0, Awesome-LLM-Reasoning is MIT. - Tags unique to awesome: awesome-list, lists, resources, unicorns. - Also covers Developer Tools. - When you need well-organized access to diverse technical subjects from IoT to robotics ## When NOT to use Awesome-LLM-Reasoning - 如果你正在寻找具体的工具或平台来直接进行LLM的训练或推理实现，而不是想要了解技术背后的理论和最近的研究成果。 - 当你寻求的是特定项目的代码库或者实际的应用实例，而非纯粹的研究性和理论性的文献收集和分析时。Awesome-LLM-Reasoning主要聚焦于提供最新的调研文章和资源链接，并不涉及具体的项目实现内容。 ## When NOT to use awesome - If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources - In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ## Common questions ### What is the difference between Awesome-LLM-Reasoning and awesome? Awesome-LLM-Reasoning: From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓. awesome: 😎 Awesome lists about all kinds of interesting topics. See the comparison table for live GitHub stats and shared categories. ### When should I choose Awesome-LLM-Reasoning over awesome? Choose Awesome-LLM-Reasoning over awesome when License: Awesome-LLM-Reasoning is MIT, awesome is CC0-1.0; Tags unique to Awesome-LLM-Reasoning: chain-of-thought, chatgpt, cot, deepseek; Also covers LLM Frameworks; 你正在寻找关于如何解锁和增强大语言模型（LLMs）和多模态大型语言模型（MLLMs）推理能力的论文和资源时。例如，如果你对理解和测试这些模型的符号推理能力感兴趣，这一资源将非常有用。. ### When should I choose awesome over Awesome-LLM-Reasoning? Choose awesome over Awesome-LLM-Reasoning when License: awesome is CC0-1.0, Awesome-LLM-Reasoning is MIT; Tags unique to awesome: awesome-list, lists, resources, unicorns; Also covers Developer Tools; When you need well-organized access to diverse technical subjects from IoT to robotics. ### When should I avoid Awesome-LLM-Reasoning? 如果你正在寻找具体的工具或平台来直接进行LLM的训练或推理实现，而不是想要了解技术背后的理论和最近的研究成果。 当你寻求的是特定项目的代码库或者实际的应用实例，而非纯粹的研究性和理论性的文献收集和分析时。Awesome-LLM-Reasoning主要聚焦于提供最新的调研文章和资源链接，并不涉及具体的项目实现内容。 ### When should I avoid awesome? If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ### Is Awesome-LLM-Reasoning or awesome more popular on GitHub? awesome has more GitHub stars (484,026 vs 3,648). Stars measure visibility, not whether either tool fits your constraints. ### Are Awesome-LLM-Reasoning and awesome open source? Yes - both are open-source projects on GitHub (Awesome-LLM-Reasoning: MIT, awesome: CC0-1.0). ### Where can I find alternatives to Awesome-LLM-Reasoning or awesome? GraphCanon lists graph-backed alternatives at [Awesome-LLM-Reasoning alternatives](/tools/atfortes-awesome-llm-reasoning/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([Awesome-LLM-Reasoning markdown twin](/tools/atfortes-awesome-llm-reasoning/alternatives.md), [awesome markdown twin](/tools/sindresorhus-awesome/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/atfortes-awesome-llm-reasoning-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Awesome-LLM-Reasoning or awesome? Awesome-LLM-Reasoning: Steady. awesome: 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 Awesome-LLM-Reasoning and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Awesome-LLM-Reasoning trust report](/tools/atfortes-awesome-llm-reasoning/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=atfortes-awesome-llm-reasoning`](/api/graphcanon/graph?tool=atfortes-awesome-llm-reasoning) - 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/_