With the development of ubiquitous computing and multimodal sensing, intelligent terminals are evolving towards a “human−machine symbiosis” paradigm, increasing demands for intelligent, autonomous, and self-adaptive terminal systems. However, existing systems still face fundamental challenges in real-world deployments: (1) Trade-off between user comfort, data fidelity, and privacy; (2) absence of context-aware scheduling mechanisms; and (3) limited capabilities in semantic generalization. To address these challenges, we propose Meta Fiberverse, a fabric-based computational platform designed for human−machine−environment symbiosis. The system integrates high-density fabric sensing, high-fidelity scheduling mechanisms, and plugin-enhanced semantic coordination framework powered by Large Language Models (LLMs). Experimental results demonstrate the system’s performance in communication latency and task accuracy, offering a feasible path and technical reference for next-generation human-centered intelligent terminals with human−machine symbiosis, resource self-consistency, and semantic autonomy.