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Xcode Hardware Performance

These are the results from running Xcode on a non-trivial open source project using various Macs. The goal is to give developers a relative idea of how each computer model compares to one another. Read the specifics and contributing sections for more info.

Xcode 9

🖥 Computer Model CPU RAM Fresh Build Time Incremental Build Time Date & Commit Hash New Build System?
⌨️ Custom PC
Early 2018
i7-8700K 4.70+ GHz 32 GB 0:36 0:07 2018-02-19 (commit)
⌨️ Custom PC
Late 2015
i7-4790k 4.0 GHz 32 GB 0:40 0:07 2018-02-22 (commit)
🖥 iMac Pro
10 Core, Late 2017
3 GHz Intel Xeon W 64 GB 0:41 0:07 2017-12-28
🖥 iMac 27"
5K 1TB SSD, Mid 2017
4,2 GHz i7 40 GB 0:49 0:08 2018-01-18
💻 MacBook Pro
Retina, 15", 2017
2.9 GHz i7 16 GB 0:49 0:16 2017-10-09 ✔️
💻 MacBook Pro
Retina, 15", 2017
2.9 GHz i7 16 GB 0:50 0:15 2017-10-09
💻 MacBook Pro
Retina, 15", Late 2013
2.6 GHz i7 16 GB 1:09 0:12 2018-02-28 ✔️
💻 MacBook Pro
Retina, 15", 2015
2.8 GHz i7 16 GB 1:17 0:12 2018-01-02
💻 MacBook Pro
Retina, 13", 2014
2.6 GHz i5 8 GB 2:30 0:23 2018-01-04
Mac Mini
Mid 2012, 512 SSD
2.3 GHz Quad-Core i7 16 GB 1:32 0:18 2017-10-20
💻 MacBook Pro
Retina, 15", 2017
2.8 GHz i7 16 GB 1:50 0:14
💻 MacBook
Retina, 15", Mid 2012
2.6 GHz i7 8 GB 2:26 0:23
💻 MacBook Pro
13", Mid 2012
2.9 GHz i7 8 GB 2:30 0:23

Xcode 8

🖥 Computer Model CPU RAM Fresh Build Time Incremental Build Time Date
🖥 iMac 5K
512GB Flash, 27", Late 2015
4.0 GHz i7 32 GB 0:28 0:06
Mac Pro
Flash Storage, Late 2013
3.5 GHz 6-Core Xeon E5 32 GB 0:30 0:05
💻 MacBook Pro
Retina, 15", Mid 2015
2.8 GHz i7 16 GB 0:39 0:07
💻 MacBook Pro
Retina, 15", Mid 2015
2.5 GHz i7 16 GB 0:42 0:09
💻 MacBook Pro
Retina, 15", Mid 2012
2.3 GHz i7 16 GB 0:46 0:08
💻 MacBook Pro
Retina, 15", Early 2013
2.4 GHz i7 8 GB 0:47 0:10
Mac Mini
Mid 2012, 512 SSD
2.3GHz Quad-Core i7 16GB 0:50 0:09
💻 MacBook Pro
Retina, 15", Mid 2014
2.2 GHz i7 16 GB 0:51 0:07
💻 MacBook Pro
Retina, 15", Late 2013
2.3 GHz i7 16 GB 0:53 0:09
🖥 iMac
HDD 1 TB, 27", Late 2012
3.4 GHz i7 8 GB 0:54 0:12
💻 MacBook Pro
Touch Bar, 15", Late 2016
2.9 GHz i7 16 GB 0:54 0:17
💻 MacBook Pro
15", Early 2011
2.0 GHz i7 8 GB 1:00 0:13
💻 MacBook Pro
15" Early 2011, SSD
2.0 GHz i7 8 GB 1:01 0:10
💻 MacBook Pro
Touch Bar, 15", Late 2016
2.9 GHz i7 16 GB 1:04 0:26
💻 MacBook Pro
13", Early 2015, 1TB SSD
3.1 Ghz i7 16 GB 1:25 0:09
💻 MacBook Pro
Retina, 13", Early 2015
2.7 GHz i5 8 GB 1:35 0:11
💻 MacBook
Retina, 12", Mid 2017
1.4 GHz i7 16 GB 1:49 0:16
💻 MacBook Pro
13", Mid 2012 256 SSD
2.5 GHz i5 8 GB 2:08 0:19
💻 MacBook Air
13", Mid 2012, 512 SSD
2 Ghz i7 8 GB 2:10 0:11
💻 MacBook
Retina, 12", Early 2016
1.2 GHz m5 8 GB 2:10 0:12
💻 MacBook Pro
13", Late 2013 256 SSD
2.4 GHz i5 8 GB 2:17 0:23
💻 MacBook
Retina, 12", Early 2015
1.2 GHz M 8 GB 2:28 0:12
💻 MacBook
Retina, 12", Early 2015
1.1 GHz M 8 GB 3:00 0:12
💻 MacBook Pro
13", Early 2011, 512 SSD
2.7 Ghz i7 8 GB 2:30 0:16
💻 MacBook Air
13", Mid 2013, 128 SSD
1.3 Ghz i5 4 GB 2:58 0:24
💻 MacBook Pro
13", Mid 2010 512 SSD
2.4 GHz Intel Core 2 Duo 8 GB 3:01 0:24
🖥 iMac
HDD 500 GB, 21.5", Mid 2010
3.06 GHz i3 12 GB 3:59 0:14
🖥 iMac
HDD 1 TB, 21.5", Late 2012
2.7 GHz i5 8 GB 4:15 0:33

Specifications

For the test, I decided to use an app that I actually work on: eidolon. Unlike most iOS apps, the project is stable and not under active development, so it's a prime candidate for accurate-ish benchmarking.

For "fresh" builds, I cleaned the build folder (⌘⇧K) repeatedly until it worked with no permissions problems. Then I sat and waited for Xcode to index the project. I also made sure the simulator was closed, so these times include booting the simulator and launching the app. Then I hit ⌘R and start a timer, only ending it when the app had fully launched.

"Incremental" builds represent a more common use case: changing one file and recompiling with the simulator already running. I added print("hello!") to application(: didFinishLaunchingWithOptions:) and hit ⌘R, timing the time it took for the app to launch.

I repeated each test a few times and took their average times.

Contributing

It would be super-cool if we could perform the above tests on a variety of machines and consolidate the results here. You can follow the instructions to download the code and the project dependencies, and send a pull request adding your own results. I'd super-appreciate it! 🙇

Please note that this project is released with a Contributor Code of Conduct. By participating in this project, you agree to abide by its terms.

License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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