--- title: "Qwen vs Chinese-LLaMA-Alpaca-2" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/qwenlm-qwen-vs-ymcui-chinese-llama-alpaca-2" tools: ["qwenlm-qwen", "ymcui-chinese-llama-alpaca-2"] --- # Qwen vs Chinese-LLaMA-Alpaca-2 *GraphCanon updated Sep 20, 2026* ## Verdict Pick Qwen if qwen is a large language model developed by Alibaba Cloud, available in Python with support for PyTorch and Transformers. It offers Docker images for easy deployment and supports various deployment options including Open; pick Chinese-LLaMA-Alpaca-2 if chinese-LLaMA-Alpaca-2 provides Chinese versions of LLaMA-2 and Alpaca-2 large language models, including long context models up to 64K. It includes pretraining. [Qwen](https://github.com/QwenLM/Qwen) reports 22k GitHub stars, 1.9k forks, and 43 open issues, last pushed Mar 5, 2026. [Chinese-LLaMA-Alpaca-2](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2) has 7.1k stars, 559 forks, and 6 open issues, last pushed Apr 19, 2026. Figures are from public GitHub metadata via [Qwen's repository](https://github.com/QwenLM/Qwen) and [Chinese-LLaMA-Alpaca-2's repository](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2). | | [Qwen](/tools/qwenlm-qwen.md) | [Chinese-LLaMA-Alpaca-2](/tools/ymcui-chinese-llama-alpaca-2.md) | | --- | --- | --- | | Tagline | Official repo of Qwen, a large language model by Alibaba Cloud | Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models | | Stars | 21,772 | 7,118 | | Forks | 1,916 | 559 | | Open issues | 43 | 6 | | Language | Python | Python | | Adopt for | Qwen is a large language model developed by Alibaba Cloud, available in Python with support for PyTorch and Transformers. It offers Docker images for easy deployment and supports various deployment options including Open | Chinese-LLaMA-Alpaca-2 provides Chinese versions of LLaMA-2 and Alpaca-2 large language models, including long context models up to 64K. It includes pretraining and instruction fine-tuning scripts, and supports various部署 | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Qwen](/tools/qwenlm-qwen.md) | [Chinese-LLaMA-Alpaca-2](/tools/ymcui-chinese-llama-alpaca-2.md) | | --- | --- | --- | | Days since push | 196d | 152d | | Open issues (now) | 43 | 6 | | Stars delta | +177 (30d) | -6 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/qwenlm-qwen/trust.md) | [trust report](/tools/ymcui-chinese-llama-alpaca-2/trust.md) | ## Decision facts: Qwen - **Requirements:** Requires Docker; Requires Python 3.8 and above.; PyTorch 1.12 and above is required, with 2.0 and above recommended.; Transformers 4.32 and above are required.; CUDA 11.4 and above are recommended for GPU users. - **Adopt for:** Qwen is a large language model developed by Alibaba Cloud, available in Python with support for PyTorch and Transformers. It offers Docker images for easy deployment and supports various deployment options including Open ## Decision facts: Chinese-LLaMA-Alpaca-2 - **Adopt for:** Chinese-LLaMA-Alpaca-2 provides Chinese versions of LLaMA-2 and Alpaca-2 large language models, including long context models up to 64K. It includes pretraining and instruction fine-tuning scripts, and supports various部署 ## Choose when ### Choose Qwen if… - Requirements: Requires Docker; Requires Python 3.8 and above.; PyTorch 1.12 and above is required, with 2.0 and above recommended.; Transformers 4.32 and above are required.; CUDA 11.4 and above are recommended for GPU users.. - Tags unique to Qwen: chinese, docker, large-language-models, llm. - When you need a large language model that supports Chinese language processing effectively. ### Choose Chinese-LLaMA-Alpaca-2 if… - Tags unique to Chinese-LLaMA-Alpaca-2: 64k, alpaca, alpaca-2, llama. - Also covers Model Training. - When you need Chinese-specific large language models with long context capabilities up to 64K. ## When NOT to use Qwen - If your project strictly requires models under a different license, as Qwen is under the Apache-2.0 License with specific commercial use agreements. - When you need a model that does not require CUDA 11.4 or above for GPU acceleration, as Qwen recommends this for optimal performance. - If your deployment environment does not support Docker, as Qwen heavily relies on Docker images for easy setup and deployment. ## When NOT to use Chinese-LLaMA-Alpaca-2 - If you need models that support languages other than Chinese, as this repository focuses on Chinese models. - If you require models with shorter context lengths than 4K, as the standard models support 4K and the long context models support 16K and 64K. - If you are looking for models that do not include human preference alignment (RLHF), as this repository includes models that have been fine-tuned for this purpose. ## Common questions ### What is the difference between Qwen and Chinese-LLaMA-Alpaca-2? Qwen: Official repo of Qwen, a large language model by Alibaba Cloud. Chinese-LLaMA-Alpaca-2: Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models. See the comparison table for live GitHub stats and shared categories. ### When should I choose Qwen over Chinese-LLaMA-Alpaca-2? Choose Qwen over Chinese-LLaMA-Alpaca-2 when Requirements: Requires Docker; Requires Python 3.8 and above.; PyTorch 1.12 and above is required, with 2.0 and above recommended.; Transformers 4.32 and above are required.; CUDA 11.4 and above are recommended for GPU users.; Tags unique to Qwen: chinese, docker, large-language-models, llm; When you need a large language model that supports Chinese language processing effectively. ### When should I choose Chinese-LLaMA-Alpaca-2 over Qwen? Choose Chinese-LLaMA-Alpaca-2 over Qwen when Tags unique to Chinese-LLaMA-Alpaca-2: 64k, alpaca, alpaca-2, llama; Also covers Model Training; When you need Chinese-specific large language models with long context capabilities up to 64K. ### When should I avoid Qwen? If your project strictly requires models under a different license, as Qwen is under the Apache-2.0 License with specific commercial use agreements. When you need a model that does not require CUDA 11.4 or above for GPU acceleration, as Qwen recommends this for optimal performance. If your deployment environment does not support Docker, as Qwen heavily relies on Docker images for easy setup and deployment. ### When should I avoid Chinese-LLaMA-Alpaca-2? If you need models that support languages other than Chinese, as this repository focuses on Chinese models. If you require models with shorter context lengths than 4K, as the standard models support 4K and the long context models support 16K and 64K. If you are looking for models that do not include human preference alignment (RLHF), as this repository includes models that have been fine-tuned for this purpose. ### Is Qwen or Chinese-LLaMA-Alpaca-2 more popular on GitHub? Qwen has more GitHub stars (21,772 vs 7,118). Stars measure visibility, not whether either tool fits your constraints. ### Are Qwen and Chinese-LLaMA-Alpaca-2 open source? Yes - both are open-source projects on GitHub (Qwen: Apache-2.0, Chinese-LLaMA-Alpaca-2: Apache-2.0). ### Where can I find alternatives to Qwen or Chinese-LLaMA-Alpaca-2? GraphCanon lists graph-backed alternatives at [Qwen alternatives](/tools/qwenlm-qwen/alternatives) and [Chinese-LLaMA-Alpaca-2 alternatives](/tools/ymcui-chinese-llama-alpaca-2/alternatives) ([Qwen markdown twin](/tools/qwenlm-qwen/alternatives.md), [Chinese-LLaMA-Alpaca-2 markdown twin](/tools/ymcui-chinese-llama-alpaca-2/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/qwenlm-qwen-vs-ymcui-chinese-llama-alpaca-2.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Qwen or Chinese-LLaMA-Alpaca-2? Qwen: Slowing. Chinese-LLaMA-Alpaca-2: 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 Qwen and Chinese-LLaMA-Alpaca-2? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Qwen trust report](/tools/qwenlm-qwen/trust); [Chinese-LLaMA-Alpaca-2 trust report](/tools/ymcui-chinese-llama-alpaca-2/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=qwenlm-qwen`](/api/graphcanon/graph?tool=qwenlm-qwen) - 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/_