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头对头基准测试
Command Code vs Muse
Command Code 记录了 2,358,177 月访问量，月度环比增长为 -12.1%，定价为免费增值，定价请咨询。Muse 记录了 45,751,822 月访问量，增长率为 +228.3%，定价为定价请咨询。
Command Code 记录了 2,358,177 月访问量，月度环比增长为 -12.1%，定价为免费增值，定价请咨询。Muse 记录了 45,751,822 月访问量，增长率为 +228.3%，定价为定价请咨询。
Muse is Meta's personal AI agent that takes on real everyday tasks — from sorting email and booking reservations to shopping, managing calendars and building fitness plans — using its own secure virtual computer in the cloud.
| 维度 / 指标 |  | |
|---|---|---|
| 官方域名 | commandcode.ai | muse.ai |
| 定价模式 | 免费增值，定价请咨询 | 定价请咨询 |
| 月访问量 | 235.82万 (2,358,177) | 4575.18万 (45,751,822) |
| 月度环比流量变化 | -32.57万 (-12.1%) | +3181.43万 (+228.3%) |
| 主要市场与份额 | 🇨🇳 中国 (47%) | 🇺🇸 美国 (53.7%) |
| 直接访问 / 月 | 174.96万 | 2732.36万 |
| 用户评分 | 4.3 | 4.5 |
| 支持的平台 | 网站 | 网站 |
会学习你编码品味的 AI 编程智能体
持续强化学习层把每一次采纳、拒绝和手动编辑变成信号，再把反复出现的模式转化为可复用的项目级技能。
自动修复格式错误的工具调用，让较弱的开放权重模型也能可靠完成智能体循环，接近前沿模型的水平。
交互式 CLI 用于结对，无头标志用于脚本化，后台沙箱智能体则用于更长时间的自主任务。
自定义 /agents 与持久化 /memory 跨会话携带项目上下文，让你不必反复解释代码库与规范。
Muse is Meta's personal AI agent that takes on real everyday tasks — from sorting email and booking reservations to shopping, managing calendars and building fitness plans — using its own secure virtual computer in the cloud.
Give Muse a goal or an everyday chore and it plans and carries out the steps itself rather than only advising you.
Each user gets a persistent, isolated Linux computer in the cloud with a full browser, so the agent can do real work online while you retain control.
Muse requests your approval before important actions such as sending an email or making a purchase, keeping you in the loop.
A complete record of what the agent has already done and what it is planning next, so its behavior stays transparent.
免费 / 开源Open-source personal AI assistant that runs locally and connects to messaging apps to automate tasks.
免费 / 开源Open-source personal AI assistant that runs locally and connects to messaging apps to automate tasks.
免费 / 开源Orchestrates multiple CLI coding agents in parallel git worktrees, but is less focused on single-user preference learning.
