MacPaw taps Liquid AI to offer on-device inference to devs building for its app store
https://techcrunch.com/2026/08/05/macpaw-taps-liquid-ai-to-offer-on-device-inference-to-devs-building-for-its-app-store/📌 【MacPaw 攜手 Liquid AI】打造裝置端推理能力，讓 AI App 也能離線運作
TL;DR：MacPaw 與 Liquid AI 合作開發 Elix 架構，為開發者提供裝置端（on-device）推理與本地記憶系統。
隨著 AI 應用進入成熟期，隱私與離線能力成為核心競爭力。烏克蘭開發商 MacPaw 正試圖改變現狀，透過與 Liquid AI 合作，將 AI 能力從雲端推向使用者的裝置端。
🤔 從雲端轉向裝置端：隱私與離線運行的關鍵
目前的 AI 應用大多依賴雲端運算，但 MacPaw 預計透過本地託管的 AI 模型，讓使用者能夠在離線狀態下執行 AI 助手與 Agentic workflows（代理工作流）。這不僅能提升隱私與安全性，更能讓裝置端的 AI 體驗更加流暢。
🧩 Liquid AI 推出 Elix 架構：針對硬體量身打造
為了實現高效能的裝置端推理，MacPaw 引入了 Liquid AI 開發的技術棧：
- Elix 系統：專門設計的裝置端推理系統（on-device inference system）。
- 本地記憶系統：提供模型本地化的記憶能力。
- 架構優化：Liquid AI 共同創辦人兼 CEO Ramin Hasani 指出，他們會根據硬體特性選擇不同的架構，以確保在裝置上運行最有效率的智能版本。
- 自適應學習：透過建立模型周邊的客製化技術棧，模型可以根據使用者輸入的數據進行改進，隨著時間推移變得更加智慧。
📊 SetApp 佈局 AI 生態：從工具轉向開發者平臺
MacPaw 不僅要升級自家產品（如 Eney 助手），更計畫透過其訂閱制 App Store —— SetApp，打造一個 AI 開發者的單一入口：
- 技術開放：一旦完成本地處理架構的開發，MacPaw 打算將這套技術開放給開發者，讓他們在開發 App 時能直接使用裝置端推理。
- 整合雲端模型：除了本地運算，該平臺未來也會整合如 Google 等公司的雲端模型，成為開發者的「一站式商店」。
- 計費模式創新：MacPaw 正在嘗試「點數制（credit-based）」定價，使用者可以根據任務的複雜程度，消耗對應數量的點數來執行 AI 操作。
🎯 實務啟示
對於開發者而言，MacPaw 的做法釋放出一個訊號：未來的 AI App 將不再僅僅是雲端 API 的封裝，能夠在裝置端高效運行、並能整合雲端與本地能力的混合架構，將成為 App Store 競爭的核心。
🔗 來源
- 標題：MacPaw taps Liquid AI to offer on-device inference to devs building for its app store
- 作者／機構：Ivan Mehta @ TechCrunch
- 連結：https://techcrunch.com/2026/08/05/macpaw-taps-liquid-ai-to-offer-on-device-inference-to-devs-building-for-its-app-store/
#AI #OnDeviceAI #LiquidAI #MacPaw #SetApp #EdgeComputing #MachineLearning #SoftwareDevelopment #Privacy #TechNews
原始資料 TechCrunch AI · 收集於 2026-08-06
摘要原文
Ukraine-based app developer MacPaw has partnered with Liquid AI to power its products with locally hosted AI models, and eventually make the tech stack available to developers. The company is also preparing its SetApp app store for AI apps with credit-based plans for users. MacPaw is currently working on its AI assistant Eney, which it unveiled last year , and now plans to build a locally hosted version, for which it has roped in Liquid AI to develop an on-device inference system called Elix as well as a local memory system. “Before training our models, we select an architecture that is different and tailored to the hardware. That allows us to really have the most efficient version of intelligence that runs directly on the device, with benefits like privacy and security,” Liquid AI’s co-founder and CEO Ramin Hasani told TechCrunch. MacPaw’s CEO Oleksandr Kosovan said locally hosted AI models will also give users the ability to run assistants and agentic workflows offline. Notably, Apple already provides its own local models to developers. But Hasani maintains that Liquid AI’s models focus on performance for different capabilities. “We are also building a customization stack around models. This means that with user input, the models can use the data and improve. We want our models to be adaptable and become more intelligent over time,” Hasani said. MacPaw plans to focus more on AI apps for its subscription-based app store, SetApp, which has over 150,000 paying users. Once it locks in the local processing architecture with Liquid AI, MacPaw wants to make the tech available to developers so they can use on-device inference with their apps. Kosovan said the platform will also provide access to other cloud models from companies like Google, acting as a one-stop shop for developers. MacPaw is already experimenting with credit-based pricing for the app store, where users can perform a certain number of AI operations based on the credits they have and the complexity of the task.
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