Differences between cloud and local models in Xcode Intelligence

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Created 2d

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I can't use cloud-based AI providers, so I'm very excited about the potential of local models with Xcode's Coding Assistant.

I've been playing around with a local MLX model, and have been generally pretty satisfied with it. But I'm curious - what features am I missing out on by using a local model instead of a larger, cloud-based model?

Is Xcode's ability to run tests, build the project, etc. limited by the use of a local model? Does it limit the ability to do more complex agentic workflows? If so, how?

Basically, local models in Xcode seem to be working pretty well for me, and I'm curious to know what cloud-based models can offer that I don't already have.

Answer 1

grid OP

2d

I was surprised not to see a local model option after installing the Xcode 27 beta. I haven't watched any of the coding assistant videos yet, (very much not interested in cloud-based AI providers) but I am also curious about whether MLX has been found to be just not as good as the cloud-based providers, or whether there is some other reason Apple decided not to include a local-model option.

Answer 2

Developer Tools Engineer OP

Apple

2d

I'm excited to hear you're exploring this! We discussed this topic quite a bit in yesterday's Coding Intelligence group lab: https://www.youtube.com/live/Vd5nu5qIhGk?si=SG0yRbHTfHwy3VxA&t=2179

I'll also try to outline what is most useful below.

When you use the mode in Xcode that lets you provide just a quick way of accessing models, that will give you the ability to "chat" with the models, and those models will get a few tools, but to get the most done, you really want the much more advanced agentic features we shipped over the last few months. This will take the number of tools that your LLM can use from a few to about 50-60 inside Xcode, as well as asking your permission to run shell commands. At that point, the possibilities are pretty unlimited.

In order to do so much more, these agentic features need a much more sophisticated coordination system at their core. They rely on another system that runs on your computer and acts as a coordinator between the LLM and the tools it can use, managing its context window and keeping it on track. These are often called "agent harnesses" and when you click the "Get" button in Xcode next to Claude Agent, Codex, or Gemini, this is what you're installing.

When commercial providers like Anthropic, OpenAI, and Google build agentic tools, it's normal for them to provide their own harness. But you are in a special situation with on-device models. You may want to connect to a different harness.

In the WWDC session on local agentic AI (https://developer.apple.com/videos/play/wwdc2026/232/), we show how to get set up with OpenCode, a popular open coding agent harness, on the command line. This is a great option to get started with, because once you are up and running, it is also immediately portable to Xcode 26.6 and Xcode 27 with ACP.

To do so:

Click "Add an agent..." in the Xcode's intelligence settings.
Go back to your command line and run which opencode.
Paste the path that you see into the "Executable" blank in the configuration.
Add acp (no dashes or slashes) as the only argument in the "Arguments" list in settings.

Now, when you make a new conversation and choose your OpenCode agent, it will have access to all of Xcode's tools and give you full agentic functionality.

Hope this helps!