A Review on Edge Large Language Models: Design, Execution, and Applications

Large language models (LLMs) have revolutionized natural language processing with their exceptional understanding, synthesizing, and reasoning capabilities. However, deploying LLMs on resource-constrained edge devices presents significant challenges due to computational limitations, memory constraints, and edge hardware heterogeneity. This survey provides a comprehensive overview of recent advancements in edge LLMs, covering the entire lifecycle—from resource-efficient model design and pre-deployment strategies to runtime inference optimizations. It also explores on-device applications across various domains. By synthesizing state-of-the-art techniques and identifying future research directions, this survey…

• NN
  National Natural Science Foundation of China

  Award: 92467301, U23A20326, 62293511, and 62372414
• KR
  Key Research and Development Program of Zhejiang Province

  Award: 2025C01061 and 2025C01012