Can MiniMax-H3 Reason About the Physical World? An Evaluation of Omni-Modal Generative Model

• 类型：arxiv
• 标识：2609.18323
• 链接：https://arxiv.org/abs/2609.18323
• 主分类：multimodal
• 形态：benchmark
• TLDR：Recent Omni-Modal Generative Models (Omni-Models) have advanced content generation toward unified modeling of text, images, video, and audio. MiniMax-H3 exemplifies this transition by combining multimodal context understanding with joint audio-visual generation in a shared latent framework. Its unified architecture raises a fundamental question: Can multimodal alignment improve the model's world reasoning, and what new evaluation paradigms do omni-modal inputs enable? To investigate this question, this work introduces a comprehensive evaluation framework organized around four complementary dim
• 副分类：evaluation
• 待LLM分类：否
• 标题中文：MiniMax-H3 能否对物理世界进行推理？一种全模态生成模型的评估
• TLDR中文：近期全模态生成模型（Omni-Models）将内容生成推进到文本、图像、视频与音频的统一建模。MiniMax-H3 体现了这一转变，在共享 latent 框架中融合多模态上下文理解与音视频联合生成。其统一架构引出一个根本性问题：多模态对齐能否提升模型的世界推理能力，全模态输入又能催生哪些新评估范式？为探究这一问题，本文提出一个围绕四个互补维度组织的全面评估框架……
• 来源文件：
• /inbox/tom/_candidates/2026-09-18-agent-rag-longcontext-candidates.json