--- title: "MiniMax-M1 vs Qwen" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/minimax-ai-minimax-m1-vs-qwenlm-qwen" tools: ["minimax-ai-minimax-m1", "qwenlm-qwen"] --- # MiniMax-M1 vs Qwen Neutral, constraint-first comparison with live GitHub stats. | | [MiniMax-M1](/tools/minimax-ai-minimax-m1.md) | [Qwen](/tools/qwenlm-qwen.md) | | --- | --- | --- | | Tagline | MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. | Official repo for Qwen, a Chinese large language model by Alibaba Cloud | | Stars | 3,158 | 21,404 | | Forks | 283 | 1,849 | | Open issues | 30 | 42 | | Language | Python | Python | | Adopt for | MiniMax-M1 is designed as the first open-weight, large-scale hybrid-attention reasoning model. It stands apart in leveraging a unique architecture that combines hybrid attention mechanisms for improved reasoning and can, | Qwen is a Chinese large language model developed by Alibaba Cloud, designed to support various formats and optimizations for natural language processing tasks. Though its official repository suggests it's no longer under | | Persona | - | - | | Runtime | - | - | | License | The repository is available under the Apache License 2.0, allowing users to utilize it freely while providing attribution as specified in the license. | Apache-2.0 | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [MiniMax-M1](/tools/minimax-ai-minimax-m1.md) | [Qwen](/tools/qwenlm-qwen.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 365d | 125d | | Open issues (now) | 30 | 42 | | Security scan | Not scanned | 44 low (44 low) | | Full report | [trust report](/tools/minimax-ai-minimax-m1/trust.md) | [trust report](/tools/qwenlm-qwen/trust.md) | **Typed relationship:** MiniMax-M1 _(successor)_ Qwen Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other. Coexists - Both models serve to advance the field of open-weight large scale reasoning models. ## Decision facts: MiniMax-M1 - **Requirements:** Min 8 GB RAM; Requires Python environment - **Adopt for:** MiniMax-M1 is designed as the first open-weight, large-scale hybrid-attention reasoning model. It stands apart in leveraging a unique architecture that combines hybrid attention mechanisms for improved reasoning and can, - **License detail:** The repository is available under the Apache License 2.0, allowing users to utilize it freely while providing attribution as specified in the license. ## Decision facts: Qwen - **Pricing:** unknown - Pricing information is not specified in the repository and depends on usage via Alibaba Cloud or APIs like HuggingFace which have their own pricing structures for model usage. - **Adopt for:** Qwen is a Chinese large language model developed by Alibaba Cloud, designed to support various formats and optimizations for natural language processing tasks. Though its official repository suggests it's no longer under ## Choose when ### Choose MiniMax-M1 if… - Requirements: Min 8 GB RAM; Requires Python environment. - Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other. - Tags unique to MiniMax-M1: reasoning-models, minimax-m1. - - Utilize when you require advanced reasoning capabilities in your AI applications due to its innovative use of hybrid attention. ### Choose Qwen if… - Pricing: Pricing information is not specified in the repository and depends on usage via Alibaba Cloud or APIs like HuggingFace which have their own pricing structures for model usage.. - Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other. - Tags unique to Qwen: pretrained-models, natural-language-processing, flash-attention, chinese-language-support. - When focusing on applications that cater primarily to the Chinese-speaking audience as Qwen is specifically optimized for the Chinese language. ## When NOT to use MiniMax-M1 - - Avoid using MiniMax-M1 if specific performance benchmarks on certain tasks have higher accuracy rates from non-hybrid, focused-attention models. - - If real-time interaction requirements are stringent, MiniMax-M1 may not be ideal due to its processing complexity and size; smaller or more streamlined models might perform better. ## When NOT to use Qwen - For projects requiring ongoing maintenance support as the repository notes a move towards Qwen2, suggesting current versions have ceased active development. - In scenarios where absolute state-of-the-art performance and recent updates for all languages are critical, due to its focus on Chinese language applications and stated obsolescence. ## Common questions ### What is the difference between MiniMax-M1 and Qwen? MiniMax-M1: MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.. Qwen: Official repo for Qwen, a Chinese large language model by Alibaba Cloud. See the comparison table for live GitHub stats and shared categories. ### When should I choose MiniMax-M1 over Qwen? Choose MiniMax-M1 over Qwen when Requirements: Min 8 GB RAM; Requires Python environment; Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other; Tags unique to MiniMax-M1: reasoning-models, minimax-m1; - Utilize when you require advanced reasoning capabilities in your AI applications due to its innovative use of hybrid attention. ### When should I choose Qwen over MiniMax-M1? Choose Qwen over MiniMax-M1 when Pricing: Pricing information is not specified in the repository and depends on usage via Alibaba Cloud or APIs like HuggingFace which have their own pricing structures for model usage.; Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other; Tags unique to Qwen: pretrained-models, natural-language-processing, flash-attention, chinese-language-support; When focusing on applications that cater primarily to the Chinese-speaking audience as Qwen is specifically optimized for the Chinese language. ### When should I avoid MiniMax-M1? - Avoid using MiniMax-M1 if specific performance benchmarks on certain tasks have higher accuracy rates from non-hybrid, focused-attention models. - If real-time interaction requirements are stringent, MiniMax-M1 may not be ideal due to its processing complexity and size; smaller or more streamlined models might perform better. ### When should I avoid Qwen? For projects requiring ongoing maintenance support as the repository notes a move towards Qwen2, suggesting current versions have ceased active development. In scenarios where absolute state-of-the-art performance and recent updates for all languages are critical, due to its focus on Chinese language applications and stated obsolescence. ### Is MiniMax-M1 or Qwen more popular on GitHub? Qwen has more GitHub stars (21,404 vs 3,158). Stars measure visibility, not whether either tool fits your constraints. ### Are MiniMax-M1 and Qwen open source? Yes - both are open-source projects on GitHub (MiniMax-M1: Apache-2.0, Qwen: Apache-2.0). ### Where can I find alternatives to MiniMax-M1 or Qwen? GraphCanon lists graph-backed alternatives at /tools/minimax-ai-minimax-m1/alternatives and /tools/qwenlm-qwen/alternatives (/tools/minimax-ai-minimax-m1/alternatives.md, /tools/qwenlm-qwen/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 /compare/minimax-ai-minimax-m1-vs-qwenlm-qwen.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, MiniMax-M1 or Qwen? MiniMax-M1: Dormant. Qwen: 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-M1 and Qwen? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: MiniMax-M1: /tools/minimax-ai-minimax-m1/trust; Qwen: /tools/qwenlm-qwen/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=minimax-ai-minimax-m1`](/api/graphcanon/graph?tool=minimax-ai-minimax-m1) - 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/_