We introduce ***FysicsWorld***, the **first** unified full-modality benchmark that supports bidirectional input–output across *image, video, audio, and text*, enabling comprehensive any-to-any evaluation across understanding, generation, and reasoning. Our systematic design spans uni-modal perception tasks to fusion-dependent reasoning under strong cross-modal coupling, allowing us to diagnose, with unprecedented clarity, the limitations and emerging strengths of modern multimodal and omni-modal architectures. In contrast to existing omni-modal and multi-modal benchmarks, our ***FysicsWorld*** has several advantages:
* **Diversity and High Quality**. ***FysicsWorld*** is characterized by **8 "*multi*"** properties, reflecting its comprehensive coverage, diversity, and robustness, namely:
*multi-dimensional* (understanding, generation, reasoning, voice interaction), *multi-modal* (text, image, video, audio as both inputs and outputs), *multi-task* (16 primary tasks, 200+ sub-tasks), *multi-source* (3,268 samples from 40+ data sources and curated web data), *multi-domain* (170+ fine-grained open-domain categories), *multi-type* (closed-ended, open-ended, multiple-choice question, and image/video/audio generation), *multi-target* (evaluates Omni-LLMs, MLLMs, modality-specific models, unified understanding–generation models), and *multi-assurance* (multi-stage quality control strategies).
* **Fusion-Dependent Cross-Modal Reasoning**. We propose a method for omni-modal data construction, which is named **C**ross-**M**odal **C**omplementarity **S**creening (**CMCS**) strategy, which ensures that our tasks maintain strong cross-modal coupling, preventing single-modality shortcuts and enforcing true synergistic perception of omni-modality.
* **Speech-Driven Cross-Modal Interaction**. To support natural, multimodal communication and interaction, we develop a speech-grounded multimodal data construction pipeline that ensures both linguistic fluency and semantic fidelity in voice-based interactions, including 10+ authentic voices and tones.
Based on ***FysicsWorld***, we extensively evaluate various advanced models, including Omni-LLMs, MLLMs, modality-specific models, and unified understanding–generation models. By establishing a unified benchmark and highlighting key capability gaps, FysicsWorld provides not only a foundation for evaluating emerging multimodal systems but also a roadmap for the next generation of full-modality architectures capable of genuinely holistic perception, reasoning, and interaction.
