AutoGLM vs iEasyRun: What's the Difference in AI Phone Control?

Where the two differ

Open-AutoGLM is an open-source Agent setup. It stresses that the model understands the interface and drives the taps. You maintain the runtime and the model connection yourself.

iEasyRun is a local AI workstation for phone automation. After you download and install it, you connect real phones and dispatch work through chat, workflows, or MCP. It is aimed at business work that involves little code.

Both can have an AI tap a phone. One leans toward a framework and research. The other leans toward a product you can hand to someone and run. Last week someone asked which to pick. I asked back: do you plan to maintain the environment yourself?

Dimension	Open-AutoGLM (AutoGLM)	iEasyRun
Setup barrier	High: dependencies, models, device debugging	Low: follow the install guide
Whether you write code	Most cases need config or code changes	The business side can use natural language and workflows
Platforms	Community practice leans toward Android experiment setups	Android / iOS / HarmonyOS
Many phones and day-to-day ops	You extend it and operate it yourself	Multi-phone management, task records, business templates
AI assistants	You connect models and the tool chain yourself	MCP can connect Claude, WorkBuddy, and others
Data	Depends on how you deploy it	Stays on the machine by default, with no server required
Who it fits	Developers, and people who want to change Agent strategy	Studios, operators, and teams that need a stable run first

Which situations each fits, and how to choose

People pick Open-AutoGLM when they need to do things like these.

• Reproduce or modify an open-source Agent.
• Swap the model, change the prompts, or change the perception and decision path.
• Accept that when the environment breaks, they fix it themselves.

In that case the freedom to change open source is the advantage. How finished the product feels comes later.

People pick iEasyRun when they need these.

• Business results such as short-video publishing, several accounts, and several phones.
• A team where not everyone can set up Python.
• Something that works after install, with data staying on their own computer.
• Phones connected to an AI assistant they already use (MCP).

Open source is useful when you need to change the code. Getting a business job online has its own timeline.

iEasyRun can connect large language models. It can also let an outside assistant drive the phones through MCP.

Research can try strategies on the open-source side. The phones that do the daily volume can run on the workstation. The two can be in use at the same time.

If the KPI is a paper, a demo, or a custom Agent, look at open source in the AutoGLM line first.

If the KPI is operating a batch of phones reliably every day, look at iEasyRun first.

To compare it with DroidRun and Mobile-Agent as well, read how to choose an open-source phone AI Agent. To install: the install guide.