How to increase MacBook artificial intelligence speed with iPhone

Backburner software details that increase artificial intelligence prefill speeds by 44 percent using iPhone 17 Pro Max and M4 Pro MacBook Pro.

Running advanced AI models like Qwen3.8-27B locally can be quite challenging depending on the amount of system memory and VRAM available. The 24GB combined memory found in M4 Pro MacBook Pro devices can create a serious bottleneck on the prefill speeds of such models.

A Reddit user came up with a different solution to this problem by connecting the iPhone 17 Pro Max model to the MacBook Pro via the USB-C port. Thanks to a special software developed, an improvement of up to 44 percent was achieved in the prefill performance of the artificial intelligence model.

Workload Sharing Between iPhone and MacBook

The developer, who goes by the username u/StayLameBro, followed a method of splitting the workload between two devices to exceed the MacBook's 24GB combined memory limit. For the prefill acceleration process, the MacBook Pro processes the first 40 layers of each group of 256 tokens and transfers this data to the iPhone.

iPhone 17 Pro Max, on the other hand, processes layers between 41 and 64 using the GPU of its own A19 Pro chip. This process takes advantage of the GPU capacity of the device, making operations approximately 2.4 times faster than working alone.

The Neural Engine unit of the device does not remain idle during this process and shortens the processing time by compiling old context data. In this way, the token writing time for a context length of 140 thousand can be reduced from 279 milliseconds to 176 milliseconds.

Performance Gains and Limits of the System

In the tests, significant speed increases were recorded in different context windows when booting a file of 2,000 tokens. In the 8K context, while the MacBook alone offered a speed of 132 tops/second, this value increased to 177 tops/second with the iPhone, a 35 percent increase.

In the 16K context, performance improved by 44 percent, from 109 toc/sec to 157 toc/sec. In the 32K context window, the speed increased from 101 tok/second to 130 tok/second, an improvement of 29 percent.

However, this method does not offer miraculous results in all cases and faces some technical limitations. For example, the iPhone does not have any accelerating effect on text rendering speeds below 64K, and this process remains entirely the responsibility of the MacBook.

It is estimated that future iPhone 18 Pro models with A20 Pro chip will be able to offer higher efficiency thanks to the dual 16-core Neural Engine structure. This hardware can provide a higher throughput on certain AI tasks compared to the current 7-core GPU.

This software, which is shared as open source on GitHub under the name of backburner, offers an experimental area for users who want to use hardware resources more efficiently. Such experimental studies reveal the potential of mobile devices to improve artificial intelligence performance.