MiniMax-M1

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    "@id": "https://agentsignals.ai/agents/minimax-m1",
    "name": "MiniMax-M1",
    "description": "MiniMax-M1 is the world's first large-scale hybrid attention inference model with open weights, developed by the MiniMax team. This model combines traditional attention mechanisms with the latest hybrid attention techniques, aiming to enhance the model's reasoning capabilities and generalization performance. It is suitable for various research and development scenarios, such as natural language processing and image recognition.",
    "url": "https://agentsignals.ai/agents/minimax-m1",
    "applicationCategory": "研究",
    "operatingSystem": "GitHub",
    "sameAs": "https://github.com/MiniMax-AI/MiniMax-M1",
    "installUrl": "https://github.com/MiniMax-AI/MiniMax-M1",
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      "price": "0",
      "priceCurrency": "USD",
      "description": "免费",
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    "featureList": [
      "Open weights",
      "Large-scale hybrid attention mechanism",
      "Strong inference capabilities"
    ],
    "datePublished": "2025-12-05T17:01:44.011739+00:00",
    "dateModified": "2025-12-19T05:06:49.741269+00:00",
    "publisher": {
      "@type": "Organization",
      "name": "Agent Signals",
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        "name": "What is MiniMax-M1?",
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          "@type": "Answer",
          "text": "The world's first open-weight large-scale hybrid attention reasoning model"
        }
      },
      {
        "@type": "Question",
        "name": "What features does MiniMax-M1 offer?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "Open weights, Large-scale hybrid attention mechanism, Strong inference capabilities"
        }
      },
      {
        "@type": "Question",
        "name": "What are the use cases for MiniMax-M1?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "Natural Language Processing, Image Recognition, Complex Dataset Analysis"
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        "name": "What are the advantages of MiniMax-M1?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "开源免费, 模型具有高度的灵活性和可扩展性, 适用于多种研究领域"
        }
      },
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        "@type": "Question",
        "name": "What are the limitations of MiniMax-M1?",
        "acceptedAnswer": {
          "@type": "Answer",
          "text": "训练资源需求高, 需要一定的技术背景来调整和优化模型"
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