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metadata
title: README
emoji: 🟧
colorFrom: gray
colorTo: red
sdk: static
pinned: false
short_description: Open-source computer use for your Mac

DeskMind 得心 — 得心,应手。

Small enough to run on your Mac. Smart enough to ask.

小到能在你的 Mac 上跑,聪明到知道该问你。

Website · 官网 · Download for Mac · GitHub · Bench

DeskMind is open-source computer use for your Mac. It reads the screen, works out the next step and acts, with small models running locally with MLX. When a task could mean two things, it asks instead of guessing.

Model What it does
brain-0.8b Fast tier: decides each step, with a probability for every option (MLX, 8-bit)
brain-4b Strong tier: checks the steps the 0.8B is unsure of (MLX, 8-bit)
eyes-4b Screen grounding: finds the target on a screenshot, for apps without an accessibility tree

Current release: G18b (revision g18b-q8, also main). On the real macOS desktop (bench v25, 13 tasks × 3 runs through the DeskMind app on an M4 Pro), the 0.8B → 4B router at threshold 0.96 passed 39 of 39 runs and never said "done" early. A decision takes about 0.5 s when the 0.8B answers and about 3.6 s when the 4B checks. Small sample; what it still gets wrong is in brain results. Any agent can use the planner through /v1/systemone.


DeskMind 得心是在你 Mac 上运行的开源电脑操作 AI:看屏幕、想下一步、动手操作,靠的是本机的小模型(MLX);任务有两种理解时, 它先问你,不瞎猜。

  • brain-0.8b:判断每一步,每个选项都给出概率;brain-4b:复核 0.8B 没把握的步骤;eyes-4b:在截图上找到要点的位置, 用于没有辅助功能结构的应用。
  • 当前版本 G18b:真实 macOS 桌面上(bench v25,13 个任务各跑 3 次,经 App 运行,M4 Pro),0.8B → 4B 路由(门槛 0.96) 39 次全部通过,没有一次没做完就说完成。样本不大,还做不好的地方见 brain results。
  • 国内下载:ModelScope 上有同样的文件(gxcsoccer/brain-0.8b、 gxcsoccer/brain-4b、 gxcsoccer/eyes-4b)。