2026驍龍峯會上，高通與PrismML在驍龍AR1 Gen 1智能眼鏡平臺本地運行20億參數1-bit量化Bonsai視覺模型，實現離線識圖問答。該模型基於Bonsai 1.7B構建，精度壓縮至1-bit，內存佔用僅爲4-bit模型四分之一，同等內存可容納約4倍參數，顯著降低存儲與推理資源需求。
蘋果正與硅谷初創公司PrismML洽談AI模型壓縮技術，目標是將大模型壓縮至iPhone本地運行，以提升隱私並推動Siri升級。PrismML CEO透露蘋果已開始評估可行性，洽談尚處早期。
科技媒體The Information報道，蘋果正接洽AI初創公司PrismML，評估在iPhone上直接運行更大規模AI模型的可行性。PrismML核心突破爲原生1-bit模型壓縮技術，可將模型體積壓縮至約1/14，內存佔用降低超90%。此舉有望實現手機端側大模型運行，實現端側AI突破。
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