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

arXiv:2609.18323 · cs.CV · Submitted 2026-09-16 · Read on arXiv

cs.CV

Submitted: 2026-09-16

Updated: 2026-09-16

Code: https://github.com/gulucaptain/MiniMax-H3-Reason

Terminology

• Generative Model — 14× in this paper · explained in 2 episodes
• Generative Models — 12× in this paper · explained in 2 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• Consistency — 9× in this paper · explained in 3 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Audio-based Disambiguation Reasoning — 5× in this paper
• World Model — 5× in this paper · explained in 7 episodes
• Benchmarking — 4× in this paper · explained in 4 episodes
• Grounding — 4× in this paper · explained in 3 episodes
• Multimodal Inputs — 4× in this paper · explained in 2 episodes
• Video-based Decision Reasoning — 4× in this paper
• Multi-view Spatial Reasoning — 3× in this paper
• Multimodal Reasoning — 3× in this paper · explained in 5 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Hallucination — 2× in this paper · explained in 4 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Decode — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Human-in-the-Loop — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Multimodal Integration — 1× in this paper · explained in 2 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes

Sources

• HiFi-UMI: Learning Deployable Manipulation Policies from High-Fidelity UMI Data Alone
• TiViBench: Benchmarking Think-in-Video Reasoning for Video Generative Models
• Do Joint Audio-Video Generation Models Understand Physics?
• TC-Bench: Benchmarking Temporal Compositionality in Text-to-Video and Image-to-Video Generation
• LTX-Video: Realtime Video Latent Diffusion
• Baichuan-Omni-1.5 Technical Report
• PhyGround: Benchmarking Physical Reasoning in Generative World Models
• RISE-Video: Can Video Generators Decode Implicit World Rules?
• Can World Simulators Reason? Gen-ViRe: A Generative Visual Reasoning Benchmark
• Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
• Ola: Pushing the Frontiers of Omni-Modal Language Model
• Humanoid Manipulation Interface: Humanoid Whole-Body Manipulation from Robot-Free Demonstrations
• Seedance 2.0: Advancing Video Generation for World Complexity
• Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
• Wan: Open and Advanced Large-Scale Video Generative Models
• Video models are zero-shot learners and reasoners
• Omni-WorldBench: Towards a Comprehensive Interaction-Centric Evaluation for World Models
• WorldMark: A Unified Benchmark Suite for Interactive Video World Models
• Qwen3 Technical Report
• HumanOmniV2: From Understanding to Omni-Modal Reasoning with Context

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