Phone Agent Comparison: AutoGLM, DroidRun, MobileAgent, iEasyRun

Two kinds of tools

Search results for “AI phone control” usually mix two kinds of options:

• Open-source agent frameworks: Open-AutoGLM, DroidRun, Mobile-Agent, and similar. They lean toward research and further development. You set up Python, the model, and the device environment yourself.
• A workstation you can run as-is: iEasyRun is the example here. It installs on your own computer, connects to real phones, and is aimed at operators, studios, and teams that want to write less code.

Both can have a model look at the screen and then tap. The way they are delivered differs a lot. Pick the wrong kind and the time goes into installing the environment and the dependencies, while the actual work has not started. Last week someone was still asking why the dependencies would not install.

Dimension	Open-AutoGLM	DroidRun	Mobile-Agent	iEasyRun
Setup barrier	High: environment, models, compatibility	High: framework and device path	High: you build the agent pipeline	Low: the downloader installs it
Coding required	Usually yes	Usually yes	Usually yes	Optional on the business side; MCP or chat is enough
Runtime	Open-source repo plus a runtime you host	Open-source framework plus self-hosting	Open-source framework plus self-hosting	Local Windows workstation
Platform focus	Often Android experiments	Often Android	Often Android research	Android / iOS / HarmonyOS
Multi-device and business use	You extend it yourself	You extend it yourself	You extend it yourself	Multi-device management, short-video workflows, and similar
AI assistant hookup	You wire the model API	You wire it	You wire it	Built-in MCP, which can connect to Claude, WorkBuddy, and similar
Data and deployment	Your own pipeline	Your own pipeline	Your own pipeline	Data stays local; no server required
Best for	Research and further development	Developers exploring a real-device agent	Algorithm and agent research	Business teams, studios, and anyone who needs a flow running first

The capability boundary of the three open-source projects moves with community versions. The table describes typical usage and how each one is delivered.

Open-AutoGLM (often called AutoGLM)

The approach is close: screenshot or UI understanding, a large model decides, then a tap carries it out. Developers who want to reproduce a paper or change the agent strategy find it handy. Operators who only want to publish videos in bulk and manage many phones often pay a high cost in environment setup.

Deep dive: How AutoGLM differs from iEasyRun.

DroidRun

This one also drives a real phone from a model. In the community it is mostly used for Android-side experiments and automation exploration. Its strength is flexibility. Multi-device work, account isolation, and business workflows are the engineering pieces you fill in yourself.

Deep dive: DroidRun compared with iEasyRun.

Mobile-Agent

The name states the position: an agent framework for phones. It fits research into how perception, planning, and execution connect. Turning that into a pipeline a studio can run steadily every day still takes a lot of engineering.

Deep dive: Mobile-Agent and iEasyRun.

What iEasyRun includes, and how to choose

iEasyRun packs install, phone connection, chat dispatch, workflows, and MCP into a product you can run:

• Completely free, and it installs on your own computer
• Real Android, iOS, and HarmonyOS phones
• Natural language and workflows; it can also connect over MCP to an AI assistant
• Lists and task records stay on the machine

Install: download and install guide.

If you want to change the agent, run experiments, and write code, use an open-source framework: AutoGLM, DroidRun, or Mobile-Agent.

If you want a business result, many phones, and less environment setup, try iEasyRun first.

If you are still looking at whether to buy Doubao hardware, read a roundup of free alternatives to the Doubao phone assistant first, then come back and decide between an open-source framework and a workstation.