--- title: "Awesome-Chinese-LLM vs Hands-On-Large-Language-Models" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aihubcn-awesome-chinese-llm-vs-handsonllm-hands-on-large-language-models" tools: ["aihubcn-awesome-chinese-llm", "handsonllm-hands-on-large-language-models"] --- # Awesome-Chinese-LLM vs Hands-On-Large-Language-Models *GraphCanon updated Aug 17, 2026* ## Verdict Pick Awesome-Chinese-LLM if awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment; pick Hands-On-Large-Language-Models if consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples. [Awesome-Chinese-LLM](https://github.com/AiHubCN/Awesome-Chinese-LLM) reports 23k GitHub stars, 2.1k forks, and 27 open issues, last pushed May 10, 2026. [Hands-On-Large-Language-Models](https://www.llm-book.com/) has 28k stars, 6.5k forks, and 38 open issues, last pushed Apr 24, 2026. Figures are from public GitHub metadata via [Awesome-Chinese-LLM's repository](https://github.com/AiHubCN/Awesome-Chinese-LLM) and [Hands-On-Large-Language-Models's repository](https://github.com/HandsOnLLM/Hands-On-Large-Language-Models). | | [Awesome-Chinese-LLM](/tools/aihubcn-awesome-chinese-llm.md) | [Hands-On-Large-Language-Models](/tools/handsonllm-hands-on-large-language-models.md) | | --- | --- | --- | | Tagline | 整理开源的中文大语言模型 | Official code repo for the O'Reilly Book - 'Hands-On Large Language Models' | | Stars | 22,738 | 28,252 | | Forks | 2,134 | 6,531 | | Open issues | 27 | 38 | | Language | - | Jupyter Notebook | | Adopt for | Awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment. | Consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples. | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 License | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Awesome-Chinese-LLM](/tools/aihubcn-awesome-chinese-llm.md) | [Hands-On-Large-Language-Models](/tools/handsonllm-hands-on-large-language-models.md) | | --- | --- | --- | | Days since push | 98d | 114d | | Open issues (now) | 27 | 38 | | Stars delta | +53 (30d) | +642 (30d) | | Open issues delta | +3 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/aihubcn-awesome-chinese-llm/trust.md) | [trust report](/tools/handsonllm-hands-on-large-language-models/trust.md) | ## Decision facts: Awesome-Chinese-LLM - **Adopt for:** Awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment. ## Decision facts: Hands-On-Large-Language-Models - **Pricing:** freemium - The repository is free and open under the Apache-2.0 license. - **Requirements:** - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial. - **Adopt for:** Consider using the 'Hands-On-Large-Language-Models' repository if your interest aligns with hands-on learning and practice of large language models through coding examples. - **License detail:** Apache-2.0 License ## Choose when ### Choose Awesome-Chinese-LLM if… - Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese, llama. - If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately. - More recently updated (last pushed May 10, 2026). ### Choose Hands-On-Large-Language-Models if… - Pricing: The repository is free and open under the Apache-2.0 license.. - Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial.. - Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large language models, llms. - - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book. ## When NOT to use Awesome-Chinese-LLM - Avoid if your project necessitates large-scale, highly advanced computational capabilities or you are working with languages other than Chinese. - If your deployment scenario is limited to public cloud services only without the option for private deployment. ## When NOT to use Hands-On-Large-Language-Models - - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book. - - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs. ## Common questions ### What is the difference between Awesome-Chinese-LLM and Hands-On-Large-Language-Models? Awesome-Chinese-LLM: 整理开源的中文大语言模型. Hands-On-Large-Language-Models: Official code repo for the O'Reilly Book - 'Hands-On Large Language Models'. See the comparison table for live GitHub stats and shared categories. ### When should I choose Awesome-Chinese-LLM over Hands-On-Large-Language-Models? Choose Awesome-Chinese-LLM over Hands-On-Large-Language-Models when Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese, llama; If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately; More recently updated (last pushed May 10, 2026). ### When should I choose Hands-On-Large-Language-Models over Awesome-Chinese-LLM? Choose Hands-On-Large-Language-Models over Awesome-Chinese-LLM when Pricing: The repository is free and open under the Apache-2.0 license.; Requirements: - Access to Jupyter Notebook is required for running code examples provided in this repository.; - Fundamental understanding of large language models and familiarity with AI concepts would be beneficial.; Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large language models, llms; - You are focusing on practical implementation aspects detailed in a structured format as outlined by O'Reilly's authoritative book. ### When should I avoid Awesome-Chinese-LLM? Avoid if your project necessitates large-scale, highly advanced computational capabilities or you are working with languages other than Chinese. If your deployment scenario is limited to public cloud services only without the option for private deployment. ### When should I avoid Hands-On-Large-Language-Models? - If you need real-time model evaluation tools rather than educational materials, as this repository primarily provides code for understanding and implementing concepts covered in a book. - You are seeking proprietary or more specialized frameworks that go beyond the examples provided in an educational context to meet specific, advanced use-case needs. ### Is Awesome-Chinese-LLM or Hands-On-Large-Language-Models more popular on GitHub? Hands-On-Large-Language-Models has more GitHub stars (28,252 vs 22,738). Stars measure visibility, not whether either tool fits your constraints. ### Are Awesome-Chinese-LLM and Hands-On-Large-Language-Models open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Awesome-Chinese-LLM or Hands-On-Large-Language-Models? GraphCanon lists graph-backed alternatives at [Awesome-Chinese-LLM alternatives](/tools/aihubcn-awesome-chinese-llm/alternatives) and [Hands-On-Large-Language-Models alternatives](/tools/handsonllm-hands-on-large-language-models/alternatives) ([Awesome-Chinese-LLM markdown twin](/tools/aihubcn-awesome-chinese-llm/alternatives.md), [Hands-On-Large-Language-Models markdown twin](/tools/handsonllm-hands-on-large-language-models/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/aihubcn-awesome-chinese-llm-vs-handsonllm-hands-on-large-language-models.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Awesome-Chinese-LLM or Hands-On-Large-Language-Models? Awesome-Chinese-LLM: Slowing. Hands-On-Large-Language-Models: 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 Awesome-Chinese-LLM and Hands-On-Large-Language-Models? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Awesome-Chinese-LLM trust report](/tools/aihubcn-awesome-chinese-llm/trust); [Hands-On-Large-Language-Models trust report](/tools/handsonllm-hands-on-large-language-models/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aihubcn-awesome-chinese-llm`](/api/graphcanon/graph?tool=aihubcn-awesome-chinese-llm) - 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/_