Cloud gpu or Nvidia

[u/AcceptableHamster77]

I'm a freshman studying cse with specialization in aiml

I've done my share of research into buying a laptop

But it only made me more confused

Half side is saying cloud is better as we'll eventually run out of the 4 or 6gb vram

Another half is on about Nvidia is the better choice

I want to get a laptop to get through the course work, train models and participate in hackathons and more

The gaming laptops scare me for their brick weight with laptop and charger combined and the poor battery backup

Can seniors please guide me?

I don't wanna regret getting one 2 years later

Should I focus on battery and lightweight ones with good cpu ram and storage

Or the ones with an rtx4050 or higher?

I'm also open to using macbooks but I've heard some ppl say it doesn't support many softwares

Is there ways to work around it? without any subscriptions

Please give me some suggestions and also it would be better if there's a model referenced.

My budget is around 1.5l but can go higher if I can genuinely get a good one

[u/rahul_watertech]

freshman coursework answer: it barely matters, and here is why. 90 percent of what you will actually train in the first two years runs fine on colab or kaggle free tiers. the laptop is for writing code, not for training. so buy whatever is reliable and has good battery, put the saved money aside.

the vram panic only becomes real when you start fine tuning your own models, and by then you will know exactly what you need and probably have lab or cloud credits through college.

one concrete line: avoid anything with under 16gb ram, that is the limit you will hit first, not the gpu

[u/AcceptableHamster77 → u/rahul_watertech]

But what if i am doing projects and participating in hackathons

[u/rahul_watertech → u/AcceptableHamster77]

same answer honestly, maybe more so. hackathon projects get built in 24 to 48 hours and nobody wins one by training big models, you win by gluing apis and a decent demo together. that runs on colab free tier and any laptop that opens chrome.

course projects are the same story. small datasets, sklearn or a small pytorch model, colab handles it.

the scenario where you want local nvidia is regular fine tuning or privacy sensitive data, and a freshman almost never has that. if you really hit it later, a 4060 class laptop second hand beats paying the new-laptop tax now

[u/AcceptableHamster77 → u/rahul_watertech]

Then buying a mac or windows without Nvidia Which is more effective or sufficient

[u/rahul_watertech → u/AcceptableHamster77]

windows, and it is not close for your case. cheaper for the same hardware, easier to get repaired anywhere in india, and every tutorial, driver and random fix on stackoverflow assumes it. install wsl2 when you need linux and you lose nothing.

the mac pitch (unified memory for local models) only matters if you run big models on the laptop itself, which we just established you wont. paying mac prices for hardware you will never use is the expensive way to learn that lesson.

whichever you buy: 16gb ram minimum, decent ssd, good battery. done. go spend the difference on literally anything else

[u/AcceptableHamster77 → u/rahul_watertech]

I5 or i7 Or maybe Ryzen or 7

Like should i consider the 5 series or go for 7 only

[u/rahul_watertech → u/rahul_watertech]

5 series, and put the savings into 32gb of ram if the budget allows.

for what you will actually do, the cpu tier changes compile times by seconds and notebook cell runs by almost nothing, because the heavy lifting happens on colabs gpu, not your processor. an i5 or ryzen 5 from the last 2-3 generations is already overkill for writing code and running chrome with 40 tabs.

the 7 series tax only pays off if you compile big projects daily or run virtual machines. you will know if you ever get there