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I recently got a laptop which I am going to use for university. It would be for CS (data science), lectures, and other miscellaneous activities. I have a 14 inch with 18 GB ram and 1 TB (SSD) of storage. But I saw that there is a 16 inch with the same core, GPU, ram but a storage of 512 GB (SSD). The 16 inch is around 1/2 kilo heavier. The price difference is less than 80 USD.

I was wondering if people could give suggestions about how much storage would be “enough” for a CS student or for programming in general for a data scientist or a software engineer. And which laptop would you recommend?

For reference these both are M3 pro Macbooks. I also mostly use a monitor at home connected to the laptop and I travel to uni roughly 3/4 days a week.

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  • Since they are both modern macbooks, you cannot upgrade storage if you are low on it. I have 1TB (as a developer student and youtuber) and I'm running kinda low, so I'm thinking of upgrading (because in my laptop you can do that)
    – Irsu85
    Nov 24, 2023 at 10:31
  • Where do you think most of your storage is going to? More towards media?
    – Ishan
    Nov 24, 2023 at 12:15
  • I think a big part is editors (both code, video and audio), VMs and dependencies of old projects that I didn't yet clean up
    – Irsu85
    Nov 25, 2023 at 10:22
  • And do you think 18gb of ram is sufficient or do you reckon I need 32
    – Ishan
    Nov 25, 2023 at 14:50
  • 16 is generally enough but if you are gonna run a lot of VMs (or in your case, emulators) for testing then you need at least 32
    – Irsu85
    Nov 26, 2023 at 8:12

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Since the upgrades are not really possible with M laptops, I usually would go for the highest package; though there is no really bad choice nowadays.

But if you are carrying the laptop a lot, mass can be critical.

In datascience, if you are running experiments on your laptop with big files, it can be interesting to choose the bigger SSD; they also have higher lifetime for same technology (TLC or QLC or MLC). Despite this, 512GB is not a bad choice; you can still store tons of videos. 2TB is definitely a choice for long years of usge and comfort.

However, the M chips, even if on the paper, they are very attractive, there can be untold and unadvertised compatibility problems at the software level; those problems tend to decrease with time, but it can be critical, so you need to verify this with actual users and the softwares you are planning to use. But the benefits (energy efficiency, battery life) can be more important. In that context, even Macbook air are also good, because of their lightweightness. If you run heaviers datascience experiments, running them on servers or on a desktop PC can help anyway.

For software engineering, sizing the CPU and RAM depend on the size of your projects. 8 cores could be right most of the time for student projets, or could be too small if you are impatient. The more and fastest you have, the less you will wait for full rebuild of you project. 32GB is not excessive, you can imagine doing mobile dev easily (Android studio, XCode).

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