--- title: "MiniMax-01 vs Chinese-LLaMA-Alpaca" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/minimax-ai-minimax-01-vs-ymcui-chinese-llama-alpaca" tools: ["minimax-ai-minimax-01", "ymcui-chinese-llama-alpaca"] --- # MiniMax-01 vs Chinese-LLaMA-Alpaca *GraphCanon updated Aug 18, 2026* ## Verdict Pick MiniMax-01 if miniMax-01 optimizes Linear Attention for large-language and vision-language models; pick Chinese-LLaMA-Alpaca if `Chinese-LLaMA-Alpaca` is a repository that includes Chinese versions of the LLaMA and Alpaca large language models, specifically designed with extended Chinese vocabulary and fine-tuned on Chinese instruction data for a. [MiniMax-01](https://www.minimax.io/) reports 3.5k GitHub stars, 332 forks, and 8 open issues, last pushed Jul 7, 2025. [Chinese-LLaMA-Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki) has 19k stars, 1.8k forks, and 6 open issues, last pushed Apr 19, 2026. Figures are from public GitHub metadata via [MiniMax-01's repository](https://github.com/MiniMax-AI/MiniMax-01) and [Chinese-LLaMA-Alpaca's repository](https://github.com/ymcui/Chinese-LLaMA-Alpaca). | | [MiniMax-01](/tools/minimax-ai-minimax-01.md) | [Chinese-LLaMA-Alpaca](/tools/ymcui-chinese-llama-alpaca.md) | | --- | --- | --- | | Tagline | Repository for MiniMax-Text-01 and MiniMax-VL-01 models based on Linear Attention | Chinese LLaMA & Alpaca Large Language Models for Local CPU/GPU Training and Deployment | | Stars | 3,463 | 18,933 | | Forks | 332 | 1,839 | | Open issues | 8 | 6 | | Language | Python | Python | | Adopt for | MiniMax-01 optimizes Linear Attention for large-language and vision-language models. | `Chinese-LLaMA-Alpaca` is a repository that includes Chinese versions of the LLaMA and Alpaca large language models, specifically designed with extended Chinese vocabulary and fine-tuned on Chinese instruction data for a | | Persona | - | - | | Runtime | - | - | | License | MIT | The repository is licensed under Apache-2.0 which allows you to use the content openly in both commercial and non-commercial projects provided you adhere to the licensing terms. | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [MiniMax-01](/tools/minimax-ai-minimax-01.md) | [Chinese-LLaMA-Alpaca](/tools/ymcui-chinese-llama-alpaca.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 406d | 119d | | Open issues (now) | 8 | 6 | | Stars delta | +17 (30d) | -9 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/minimax-ai-minimax-01/trust.md) | [trust report](/tools/ymcui-chinese-llama-alpaca/trust.md) | ## Decision facts: MiniMax-01 - **Adopt for:** MiniMax-01 optimizes Linear Attention for large-language and vision-language models. ## Decision facts: Chinese-LLaMA-Alpaca - **Pricing:** freemium - Access to `Chinese-LLaMA-Alpaca` models and documentation is free, but commercial usage should adhere to open-source licensing requirements. - **Adopt for:** `Chinese-LLaMA-Alpaca` is a repository that includes Chinese versions of the LLaMA and Alpaca large language models, specifically designed with extended Chinese vocabulary and fine-tuned on Chinese instruction data for a - **License detail:** The repository is licensed under Apache-2.0 which allows you to use the content openly in both commercial and non-commercial projects provided you adhere to the licensing terms. ## Choose when ### Choose MiniMax-01 if… - License: MiniMax-01 is MIT, Chinese-LLaMA-Alpaca is Apache-2.0. - Tags unique to MiniMax-01: llm, vision-language-model, vlm. - When high throughput performance is required for model serving ### Choose Chinese-LLaMA-Alpaca if… - License: Chinese-LLaMA-Alpaca is Apache-2.0, MiniMax-01 is MIT. - Pricing: Access to `Chinese-LLaMA-Alpaca` models and documentation is free, but commercial usage should adhere to open-source licensing requirements.. - Tags unique to Chinese-LLaMA-Alpaca: alpaca, llama, nlp, pre-trained-language-models. - You should consider using `Chinese-LLaMA-Alpaca` if your project involves local deployment and training using CPUs or GPUs, particularly if the focus is on Chinese language texts. These models are pre ## When NOT to use MiniMax-01 - If deep customization of attention mechanisms aside from Linear Attention is needed - In favor of frameworks lacking vLLM's optimization features, when efficiency or memory use are secondary to flexibility ## When NOT to use Chinese-LLaMA-Alpaca - `Chinese-LLaMA-Alpaca` might not be the best fit if your project requires extensive multi-language support beyond Chinese. - If you are exclusively targeting markets where English is the primary language, and fine-tuning or additional pre-training on Chinese data does not add value to your application. - Avoid using this tool if you require a model that has been extensively trained across global datasets for broad international comprehension, as `Chinese-LLaMA-Alpaca` is focused heavily on Chinese. ## Common questions ### What is the difference between MiniMax-01 and Chinese-LLaMA-Alpaca? MiniMax-01: Repository for MiniMax-Text-01 and MiniMax-VL-01 models based on Linear Attention. Chinese-LLaMA-Alpaca: Chinese LLaMA & Alpaca Large Language Models for Local CPU/GPU Training and Deployment. See the comparison table for live GitHub stats and shared categories. ### When should I choose MiniMax-01 over Chinese-LLaMA-Alpaca? Choose MiniMax-01 over Chinese-LLaMA-Alpaca when License: MiniMax-01 is MIT, Chinese-LLaMA-Alpaca is Apache-2.0; Tags unique to MiniMax-01: llm, vision-language-model, vlm; When high throughput performance is required for model serving. ### When should I choose Chinese-LLaMA-Alpaca over MiniMax-01? Choose Chinese-LLaMA-Alpaca over MiniMax-01 when License: Chinese-LLaMA-Alpaca is Apache-2.0, MiniMax-01 is MIT; Pricing: Access to `Chinese-LLaMA-Alpaca` models and documentation is free, but commercial usage should adhere to open-source licensing requirements.; Tags unique to Chinese-LLaMA-Alpaca: alpaca, llama, nlp, pre-trained-language-models; You should consider using `Chinese-LLaMA-Alpaca` if your project involves local deployment and training using CPUs or GPUs, particularly if the focus is on Chinese language texts. These models are pre. ### When should I avoid MiniMax-01? If deep customization of attention mechanisms aside from Linear Attention is needed In favor of frameworks lacking vLLM's optimization features, when efficiency or memory use are secondary to flexibility ### When should I avoid Chinese-LLaMA-Alpaca? `Chinese-LLaMA-Alpaca` might not be the best fit if your project requires extensive multi-language support beyond Chinese. If you are exclusively targeting markets where English is the primary language, and fine-tuning or additional pre-training on Chinese data does not add value to your application. Avoid using this tool if you require a model that has been extensively trained across global datasets for broad international comprehension, as `Chinese-LLaMA-Alpaca` is focused heavily on Chinese. ### Is MiniMax-01 or Chinese-LLaMA-Alpaca more popular on GitHub? Chinese-LLaMA-Alpaca has more GitHub stars (18,933 vs 3,463). Stars measure visibility, not whether either tool fits your constraints. ### Are MiniMax-01 and Chinese-LLaMA-Alpaca open source? Yes - both are open-source projects on GitHub (MiniMax-01: MIT, Chinese-LLaMA-Alpaca: Apache-2.0). ### Where can I find alternatives to MiniMax-01 or Chinese-LLaMA-Alpaca? GraphCanon lists graph-backed alternatives at [MiniMax-01 alternatives](/tools/minimax-ai-minimax-01/alternatives) and [Chinese-LLaMA-Alpaca alternatives](/tools/ymcui-chinese-llama-alpaca/alternatives) ([MiniMax-01 markdown twin](/tools/minimax-ai-minimax-01/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/minimax-ai-minimax-01-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, MiniMax-01 or Chinese-LLaMA-Alpaca? MiniMax-01: Dormant. 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 MiniMax-01 and Chinese-LLaMA-Alpaca? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [MiniMax-01 trust report](/tools/minimax-ai-minimax-01/trust); [Chinese-LLaMA-Alpaca trust report](/tools/ymcui-chinese-llama-alpaca/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=minimax-ai-minimax-01`](/api/graphcanon/graph?tool=minimax-ai-minimax-01) - 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/_