端側大模型迎突破！Liquid AI 開源混合專家模型 LFM2.5
重點摘要
人工智能初創公司Liquid AI發佈並開源了端側大模型LFM2.5-8B-A1B，專為消費級硬件設計，優化工具調用和指令遵循能力。該模型採用稀疏混合專家架構，總參數量8.3B，但每個Token僅激活1.5B參數，在降低計算成本的同時提升推理性能，可流暢運行於手機和筆記本電腦上。
### 重點整理：Liquid AI 端側大模型 LFM2.5 開源
人工智慧新創公司 Liquid AI 近日宣布開源其最新端側大語言模型 LFM2.5-8B-A1B，專為消費級硬體設計。這款模型主打優化工具調用與指令遵循能力，採用稀疏混合專家架構，總參數量達 8.3B，但每個 token 僅激活 1.5B 參數，大幅降低計算與記憶體需求，目標是在手機、筆記型電腦上流暢運行本地端 AI。
### 技術亮點：稀疏混合專家架構的突破
LFM2.5 的核心技術在於稀疏混合專家（SMoE）架構。傳統密集模型雖參數龐大，但計算成本高昂；SMoE 則透過動態選擇專家子網路，僅針對當下 token 激活部分
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