The development of large language models (LLMs) has given rise to four major application paradigms: LLM app stores, LLM agents, self-hosted LLM services, and LLM-powered devices. Each has its advantages but also shares common challenges. LLM app stores lower the barrier to development but lead to platform lock-in; LLM agents provide autonomy but lack a unified communication mechanism; self-hosted LLM services enhance control but increase deployment complexity; and LLM-powered devices improve privacy and real-time performance but are limited by hardware. This paper reviews and analyzes these paradigms, covering architecture design, application ecosystem, research progress, as well as the challenges and open problems they face. Based on this, we outline the next frontier of LLM applications, characterizing them through three interconnected layers: infrastructure, protocol, and application. We describe their responsibilities and roles of each layer and demonstrate how to mitigate existing fragmentation limitations and improve security and scalability. Finally, we discuss key future challenges, identify opportunities such as protocol-driven cross-platform collaboration and device integration, and propose a research roadmap for openness, security, and sustainability.