--- title: "Awesome-Chinese-LLM vs Chinese-LLaMA-Alpaca" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aihubcn-awesome-chinese-llm-vs-ymcui-chinese-llama-alpaca" tools: ["aihubcn-awesome-chinese-llm", "ymcui-chinese-llama-alpaca"] --- # Awesome-Chinese-LLM vs Chinese-LLaMA-Alpaca *GraphCanon updated Sep 20, 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 Chinese-LLaMA-Alpaca if chinese-LLaMA-Alpaca offers Chinese versions of LLaMA and Alpaca models, with expanded Chinese vocabulary and pre-training on Chinese data, supporting local deployment on CPU/GPU. [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. [Chinese-LLaMA-Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki) has 19k stars, 1.8k forks, and 5 open issues, last pushed Apr 19, 2026. Figures are from public GitHub metadata via [Awesome-Chinese-LLM's repository](https://github.com/AiHubCN/Awesome-Chinese-LLM) and [Chinese-LLaMA-Alpaca's repository](https://github.com/ymcui/Chinese-LLaMA-Alpaca). | | [Awesome-Chinese-LLM](/tools/aihubcn-awesome-chinese-llm.md) | [Chinese-LLaMA-Alpaca](/tools/ymcui-chinese-llama-alpaca.md) | | --- | --- | --- | | Tagline | 整理开源的中文大语言模型 | Chinese LLaMA & Alpaca LLMs | | Stars | 22,738 | 18,943 | | Forks | 2,134 | 1,836 | | Open issues | 27 | 5 | | Language | - | Python | | Adopt for | Awesome-Chinese-LLM is a curated list focusing on smaller, less computationally expensive Chinese language models suitable for private deployment. | Chinese-LLaMA-Alpaca offers Chinese versions of LLaMA and Alpaca models, with expanded Chinese vocabulary and pre-training on Chinese data, supporting local deployment on CPU/GPU. | | Persona | - | - | | Runtime | - | - | | License | - | The tool is licensed under Apache-2.0, allowing for free use, modification, and distribution. | | Categories | LLM Frameworks, Model Training | Inference & Serving, 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) | [Chinese-LLaMA-Alpaca](/tools/ymcui-chinese-llama-alpaca.md) | | --- | --- | --- | | Days since push | 98d | 152d | | Open issues (now) | 27 | 5 | | Stars delta | +53 (30d) | +10 (30d) | | Open issues delta | +3 (30d) | -1 (30d) | | Full report | [trust report](/tools/aihubcn-awesome-chinese-llm/trust.md) | [trust report](/tools/ymcui-chinese-llama-alpaca/trust.md) | ## Shared compatibility - **LangChain**: [Awesome-Chinese-LLM](/tools/aihubcn-awesome-chinese-llm.md) - LangChain integration; [Chinese-LLaMA-Alpaca](/tools/ymcui-chinese-llama-alpaca.md) - LangChain integration ## 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: Chinese-LLaMA-Alpaca - **Pricing:** freemium - The repository provides free access to the models and scripts, but users may incur costs related to hardware and cloud services for deployment. - **Requirements:** Min 8 GB RAM; Requires Python environment.; Supports deployment on local CPU/GPU. - **Adopt for:** Chinese-LLaMA-Alpaca offers Chinese versions of LLaMA and Alpaca models, with expanded Chinese vocabulary and pre-training on Chinese data, supporting local deployment on CPU/GPU. - **License detail:** The tool is licensed under Apache-2.0, allowing for free use, modification, and distribution. ## Choose when ### Choose Awesome-Chinese-LLM if… - Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese. - If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately. - More GitHub stars (23k vs 19k) - visibility, not fit. ### Choose Chinese-LLaMA-Alpaca if… - Pricing: The repository provides free access to the models and scripts, but users may incur costs related to hardware and cloud services for deployment.. - Requirements: Min 8 GB RAM; Requires Python environment.; Supports deployment on local CPU/GPU.. - Tags unique to Chinese-LLaMA-Alpaca: alpaca, lora, plm, pre-trained-language-models. - Also covers Inference & Serving. - When you need Chinese-specific large language models for tasks that require deep understanding of the Chinese language. ## 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 Chinese-LLaMA-Alpaca - If your project requires models that are not specific to the Chinese language or do not benefit from Chinese-specific pre-training. - When you need models that are not available in the sizes provided by Chinese-LLaMA-Alpaca, such as models smaller than 7B or larger than 33B. - If you prefer models that are not based on LLaMA or Alpaca architectures. ## Common questions ### What is the difference between Awesome-Chinese-LLM and Chinese-LLaMA-Alpaca? Awesome-Chinese-LLM: 整理开源的中文大语言模型. Chinese-LLaMA-Alpaca: Chinese LLaMA & Alpaca LLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose Awesome-Chinese-LLM over Chinese-LLaMA-Alpaca? Choose Awesome-Chinese-LLM over Chinese-LLaMA-Alpaca when Tags unique to Awesome-Chinese-LLM: awesome-lists, chatglm, chinese; If you are looking to implement low-cost and efficient Chinese NLP solutions that can be deployed privately; More GitHub stars (23k vs 19k) - visibility, not fit. ### When should I choose Chinese-LLaMA-Alpaca over Awesome-Chinese-LLM? Choose Chinese-LLaMA-Alpaca over Awesome-Chinese-LLM when Pricing: The repository provides free access to the models and scripts, but users may incur costs related to hardware and cloud services for deployment.; Requirements: Min 8 GB RAM; Requires Python environment.; Supports deployment on local CPU/GPU.; Tags unique to Chinese-LLaMA-Alpaca: alpaca, lora, plm, pre-trained-language-models; Also covers Inference & Serving; When you need Chinese-specific large language models for tasks that require deep understanding of the Chinese language. ### 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 Chinese-LLaMA-Alpaca? If your project requires models that are not specific to the Chinese language or do not benefit from Chinese-specific pre-training. When you need models that are not available in the sizes provided by Chinese-LLaMA-Alpaca, such as models smaller than 7B or larger than 33B. If you prefer models that are not based on LLaMA or Alpaca architectures. ### Is Awesome-Chinese-LLM or Chinese-LLaMA-Alpaca more popular on GitHub? Awesome-Chinese-LLM has more GitHub stars (22,738 vs 18,943). Stars measure visibility, not whether either tool fits your constraints. ### Are Awesome-Chinese-LLM and Chinese-LLaMA-Alpaca open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Awesome-Chinese-LLM or Chinese-LLaMA-Alpaca? GraphCanon lists graph-backed alternatives at [Awesome-Chinese-LLM alternatives](/tools/aihubcn-awesome-chinese-llm/alternatives) and [Chinese-LLaMA-Alpaca alternatives](/tools/ymcui-chinese-llama-alpaca/alternatives) ([Awesome-Chinese-LLM markdown twin](/tools/aihubcn-awesome-chinese-llm/alternatives.md), [Chinese-LLaMA-Alpaca markdown twin](/tools/ymcui-chinese-llama-alpaca/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-ymcui-chinese-llama-alpaca.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 Chinese-LLaMA-Alpaca? Awesome-Chinese-LLM: Slowing. Chinese-LLaMA-Alpaca: 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 Chinese-LLaMA-Alpaca? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Awesome-Chinese-LLM trust report](/tools/aihubcn-awesome-chinese-llm/trust); [Chinese-LLaMA-Alpaca trust report](/tools/ymcui-chinese-llama-alpaca/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/_