MacBook Air M2 for Programming [Apple M2 Review]

00:04:39
https://www.youtube.com/watch?v=hzyO3INhoS0

Summary

TLDRThe video explores whether the M2 MacBook Air is suitable for programming. Despite being a great laptop with an efficient Unix shell, it lacks the performance needed for intense tasks like AI and machine learning compared to models like M2 Pro. It smoothly runs Xcode, even outperforming older, more RAM-heavy MacBook Pros. For web developers, VS Code runs excellently, and a speedometer benchmark shows notable improvement over older models. The laptop manages to run Python and TensorFlow but performs slower than the M2 Pro. One limitation is its inability to support dual external monitors. Overall, it's a good choice for programming but not as powerful as more advanced models.

Takeaways

  • 💻 The M2 MacBook Air runs Xcode smoothly, outperforming older MacBook Pros.
  • ⚡ Speedometer benchmark score indicates improved performance over older MacBooks.
  • 🧠 Less effective for AI than desktops or M2 Pro despite being a good laptop.
  • 🖥️ Supports only one external monitor, not ideal for dual setups.
  • 🐍 Handles Python and TensorFlow but slower than M1 Pro.
  • 💡 Unix shell in MacBook enhances versatility in programming.
  • 💼 Suitable for coding, but for intensive tasks, consider M2 Pro.
  • 🔍 Testing included VS Code, revealing strong performance for web applications.

Timeline

  • 00:00:00 - 00:04:39

    The speaker evaluates the M2 MacBook Air for programming, using the 10-core GPU and 8 GB RAM model. Initial tests on past iOS projects and Xcode show a smooth performance, exceeding a 2019 16-inch MacBook Pro with 32 GB RAM in speed. To further assess Xcode performance, the speaker uses an Xcode benchmark project from GitHub. After preparing the MacBook, test results indicate a build time of 134 seconds, aligning closely with the M1 MacBook Pro's performance after a re-test.

Mind Map

Video Q&A

  • Is the M2 MacBook Air suitable for programming?

    Yes, but it may not be as powerful as the M2 Pro for more intensive tasks like AI and machine learning.

  • How does the M2 MacBook Air perform with Xcode?

    It runs Xcode smoothly and compiles projects faster than older MacBook Pros with higher RAM.

  • Can the M2 MacBook Air support dual external monitors?

    No, it only supports one external monitor.

  • What is the speedometer benchmark score for web applications?

    The M2 MacBook Air scored 343 runs per minute.

  • Does the M2 MacBook Air run AI applications effectively?

    It is less effective for AI work compared to desktops or models like the M2 Pro.

  • What Unix features does the M2 MacBook Air provide?

    MacOS being a Unix system offers a developer-friendly shell, supporting multiple programming languages.

  • What are the coding benefits of using a MacBook?

    Its Unix shell and ability to run multiple programming languages without specialized IDEs are beneficial.

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  • 00:00:00
    foreign
  • 00:00:18
    the m2 macbook air is a great laptop but
  • 00:00:21
    isn't good for programmers i will try to
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    answer that question in this video
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    before we get started i want to specify
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    that this is the m2 air with 10 core gpu
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    and 8 gigabytes of ram
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    i tried some of my past ios projects and
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    everything runs smoothly i have not
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    experienced any freezes on xcode itself
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    and have been able to run the simulator
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    with no issues
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    as mentioned in the first impressions
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    video i made for this macbook it
  • 00:00:45
    actually compiles and runs the project
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    faster than on my 2019 16-inch macbook
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    pro which has 32 gigabytes of ram
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    however i wanted a more general way of
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    testing xcode so that i can better
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    relate the performance to you guys so i
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    decided to clone this xcode benchmark
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    project from github
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    xcode benchmark is a large code base to
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    measure the compilation time in xcode
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    and compare the performance with that of
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    other popular apple computers
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    i followed the instructions before
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    running the test by turning off the
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    wi-fi disabling all software running at
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    startup updating the battery settings
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    and rebooting the mac
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    now that the macbook was plugged in i
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    was finally ready to run the test
  • 00:01:27
    the build time of 134 seconds with the
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    m2 macbook air just below the m1 macbook
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    pro
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    i wasn't too satisfied with that result
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    so decided to run it again
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    this time i got a much better result of
  • 00:01:43
    130 seconds which puts it on par with
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    the m1 macbook pro
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    i know a lot of you watching might be
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    web developers so i wanted to do some
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    tests for you as well
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    first up i decided to use vs code as i
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    know this is probably the most popular
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    code editor for web applications however
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    because vs code is very lightweight it
  • 00:02:01
    will run well on pretty much any laptop
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    i decided to run the speedometer browser
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    benchmark which measures the
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    responsiveness of web applications
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    it does so by using demo web
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    applications to simulate user actions
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    such as adding to-do items
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    on the m2 macbook air i got a score of
  • 00:02:18
    343 runs per minute
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    in comparison my 2015 13-inch macbook
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    pro has 102 runs per minute
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    this means you will likely see an
  • 00:02:28
    improvement from the older macbooks even
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    for web development
  • 00:02:32
    i know python and artificial
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    intelligence are very popular among
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    developers these days so i went ahead
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    and downloaded pycharm as well as
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    anaconda to run some python and
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    tensorflow benchmark test
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    first i ran the python bundle broad
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    algorithm which stresses the cpu to test
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    how powerful it is the program runs in 1
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    minute and 41 seconds which is
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    significantly slower than the 14 inch m1
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    pro for example which runs it in one
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    minute
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    then i found ai benchmark alpha which is
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    an open source python library for
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    evaluating ai performance of various
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    platforms including cpus gpus and tpus
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    the tests cover all major deep learning
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    tasks and architectures making it useful
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    for researchers developers and anyone
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    running ai applications on their devices
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    with a device ai score of 235 the m2 air
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    is at the bottom of the ranks below the
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    intel core i7 930 with 288
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    so if you want to work on ai you're
  • 00:03:29
    probably better off with a desktop
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    computer
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    i also ran an auto encoder from
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    tensorflow i went ahead and set up the
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    anaconda environment on my macbook in
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    order to run the auto encoder
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    i ran the code with 10 input images and
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    it took the neural network 1 minute and
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    13 seconds to reconstruct these images
  • 00:03:48
    i think most of you will agree that when
  • 00:03:50
    it comes to programming on a macbook the
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    best part of it is the unix shell
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    macos is a fully featured unix operating
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    system which makes the shell very
  • 00:03:58
    developer friendly it is very useful for
  • 00:04:00
    a programmer as it lets you run programs
  • 00:04:02
    in almost any language without using a
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    specialized ide
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    if not from macbook developers would
  • 00:04:08
    otherwise need to dual boot linux and
  • 00:04:09
    windows to get some of the same
  • 00:04:10
    experience
  • 00:04:12
    i know that a lot of programmers like
  • 00:04:14
    using dual monitor setups when coding so
  • 00:04:16
    it is important to note that the m2
  • 00:04:18
    macbook air just like the m1 air only
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    support one external monitor if you want
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    to use dual external monitors this is
  • 00:04:25
    not the macbook for you
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    in conclusion the m2 air is a good
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    laptop for programming but definitely
  • 00:04:31
    not on the level of the m2 pro
  • 00:04:32
    especially considering the price
  • 00:04:34
    difference is not too big thank you for
  • 00:04:36
    watching and see you in the next video
Tags
  • M2 MacBook Air
  • programming
  • performance
  • Xcode
  • AI
  • Unix Shell
  • dual monitor