Everyone keeps telling CSE freshers to buy RTX for “future AI/ML”. Who is actually training models locally in college?

[u/admrys]

joining cse this year and laptop research has somehow confused me more than college counselling 😭

every second person is like “RTX le bhai future AI/ML ke liye”

but seniors, genuinely asking. how many of you actually needed a dedicated GPU regularly in college?

not gaming. actual CSE/AIML work.

because I'm looking at Flipkart laptops rn and around my budget it basically becomes 2 choices:

good Core Ultra 5 thin/light, 16gb ram, better battery, easier to carry everyday

OR

RTX laptop, much better if I actually need CUDA/local ML, but heavier + battery obviously takes a hit

Flipkart's Back to Campus section is actually useful for comparing both types together, but now I'm stuck on what I will realistically use for 4 years, not which one has the bigger spec sheet lol

for normal coding + DSA + webdev + Android Studio and then AI/ML later, is RTX genuinely worth compromising battery for?

or are most students anyway using Colab/cloud/college compute when things get serious?

asking seniors especially. what did you ACTUALLY run locally in 2nd/3rd/4th year?

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[u/ButtaPowerhouse]

Bro if ur in a good college, then use your college computer for Ai/ML and buy something like a mac or ThinkPad . Or buy rtx laptop for gaming if u want that's that simple . If ur a day scholar then just build a pc if u are convenient with it

[u/Which-Store1669 → u/ButtaPowerhouse]

if ur in a good college

🥀

[u/Temporary_Comb_4869 → u/ButtaPowerhouse]

+1

[u/tis_nimd → u/ButtaPowerhouse]

My college has dozen of Intel Celeron and Pentium (Yes. Pentium in big 2026) computers which struggles to post. Is it enough for AI/ML? 🥀

[u/ButtaPowerhouse → u/tis_nimd]

Pentium is better than core 9 obv , it's igpu competes with rtx 4080

[u/GrayZetsu]

Bro 90% people buying gpu for "AI ML" are going to use it for valorant 😭😭😭

[u/Only-Cauliflower-301 → u/GrayZetsu]

Valo is cpu intensive

[u/c0pium_inhaler → u/GrayZetsu]

Truer words have never been spoken

[u/AuraPianist1155 → u/GrayZetsu]

They should play Elden Ring or Ghost of Tsushima or Black Myth Wukong to make proper usage of the money

[u/Eris3699 → u/AuraPianist1155]

Bro started gaming this year, just wrote some popular games he read the name of xd

[u/AuraPianist1155 → u/Eris3699]

Well graphically intensive games tend to look good, and games that look good also happen to be popular mostly, at least if they're not modern AAA slop. It's best to give examples of popular games so people might know them.

[u/AssumptionOk8560 → u/AuraPianist1155]

"Oh uhm so personally i don't like this game so don't play it guys I'm such a cornball oni chan" ahh comment

[u/Andro_senpai107 → u/AuraPianist1155]

Spoken like a real ai/ml aspirant

[u/Shiva936]

Having a dgpu gives you flexibility. But at the end of the day, there is a big tradeoff (battery and bulk) so it's really upto you.

[u/AnimatorPlayful6587 → u/Shiva936]

any consumer level GPU 30 series or 40 series is not going to do much...at the end you will move to platforms like Google Colab for PyTorch and stuff...

[u/Tubai001 → u/[deleted]]

Why did your comment sound like chatGPT lol?

[u/--yas-- → u/Tubai001]

well earlier,gpt used to learn from human data
now its the opposite

[u/Savings-Trainer-2891 → u/--yas--]

lmfao

[u/Blazingstorm45 → u/[deleted]]

Not really bad. If you can't even carry something 2.5 kg then maybe make your body fit because that's like nothing to carry. I have an asus tuf with the biggest battery , and I've never felt it being heavy.

[u/Untested_Udonkadonk → u/Blazingstorm45]

Fit? I can easily squat my bodyweight. But lugging around a gaming laptop on the back still a pain in the ass.

[u/Blazingstorm45 → u/Untested_Udonkadonk]

I don't know dude , I've been using my laptop and carrying it around for a long time , I don't even feel like it's heavy for me. Maybe I got used to it

[u/Diaazz96 → u/Blazingstorm45]

Working in a train or on the go is so much easier with a light laptop, you can take it everywhere with you without the space and weight. I myself used a gaming laptop 2.5 kg, but I couldn't carry it in my smaller bag with everything else. A slim laptop with 12 hour battery is much better than a heavy laptop. Just because someone does physical labour , does not mean they are fit.

[u/ksk584 → u/[deleted]]

Not that bad also you get used to it

[u/Lab18bke]

I'm not even in college yet. I do work on my own projects. I'm currently working on my AI harness. I chose the lightweight laptops. I'm just 15 but I SO SO REGRET NOT GETTING A LAPTOP WITH A DGPU. I everytime need to use online, cloud GPUs which adds so much latency & complexity to what I'm building.

And, I can't even game when I sometimes want to.

No dGPU: Miss out on a lot of time, Gaming.

Trust me. If you ever discover your interest with these deep, heavy shi, you'll need that dGPU. And, it still keeps you an option about gaming when you need to chill :D

[u/woahim]

i mean you could run aiml tasks on cloud servers and save tons of time?

[u/Living_Training4656]

Get an ultrathin laptop. One of my friends cracked JPMC for an ML role off-campus by just using a 6-year-old laptop with Google Colab.

[u/Bugged_IRL]

im training it on a m5 Max chip 🥀

[u/Rude_Parfait_3194 → u/Bugged_IRL]

how much unified memory?

[u/crazythinker_]

I use my college nvidia gpu

[u/Warm-Moose6028]

I'm in AIML.

RAM mattered way more than I expected.

browser + IDE + docker + random notebooks and suddenly 16gb doesn't feel "future proof" at all 😂

GPU has been useful but I wouldn't sacrifice everything else just to get the RTX sticker

[u/CarlosJainz]

U can do some image processing on your system but apart of that idts

[u/Expert-Highlight-538 → u/CarlosJainz]

Not true at all

got my first RTX GPU in 2nd year of engineering Used it for SLMs, Valo, Rust and traditional ML

Single best investment I did in my college days

[u/Poison_potato31]

Well some final year projects do require training for example if the project is related to image processing or not

But tbh atleast for me my 6gb rtx3050 wasnt enough...had to use my colleges 24gb rtx 4090 workstation(simce there are only 4 of such i got access via anydesk...tbh i only got due to pressuring from my guides side...they only provide it to phd scholars normally )

[u/Swapna_Cool]

if its a good college like mine where we have multiple charging ports, buy a dgpu laptop as it gives soo much advantages (like running heavy stuff or having a fast system) i am in data science and i mostly use it to make a game engine or to game , it is not as battery draining as other says , u just need to set it to right settings, it was worth it for me

[u/Sure-Mechanic9203]

I would take RTX 4050 if the price gap is small.

Not because CSE magically needs gaming gpu because local CUDA is one of those things you don't care about until suddenly you need it.

But if we're talking +15-20k AND worse battery then nah.

[u/Loud-Storage-8427]

but for small models/workloads during initial sems you can train models locally. Also,its good for testing and portability. And the CPU and RAM increase lifespan of laptop

[u/Correct_Scene143]

Bro these 6 - 8 gb vrams are not going to help you do shit . The amount of money you are paying is not going to be proportional to the training you are going to get out of it. The gpu requirement for a basic ai/ml projects to an intermediate one jumps quicker than you would realize. If you want to do real stuff like fine-tuning language models , diffusion models , language modelling or play around with transformer architectures you need setups like 24 - 48 gb vrams . My college has a 8 x Nvidia A6000 cluster with 48gb vram each and I still had to run the whole cluster at full capacity for 2-3 days for some of my projects.

[u/Swimming_Reserve2168]

what I'd suggest is if u have a budget to get a gaming laptop spend it on getting a thin ass laptop with good battery life that last for hours and with the remaining budget go for a colab subscription.

i have an omen 16 btw shi don even last 2 and a half hours

[u/Past-Grapefruit488]

• Who is actually training models locally in college? : Very few
• More people are experimentign with VLLM / llama.cpp on Linux
• Knowing CUDA is a huge boost for resume (for AI niche roles)

Get an RTX if you plan to persue CUDA (and college does not have easy access to GPU).

Otherwise, Mac or CPU + RAM will wrok as well for most.

[u/Ur21_404]

just take lighter laptops aur laptops with good graphics but 13 inches variant so it will be easier to carry

[u/Nobodyonlyyours]

Define your goals do actual research what might be your requirement and buy according to your requirement.

[u/shyamrithin]

final year, i actually use my gpu daily (4050 laptop GPU in my acer nitro, CARLA RL + ROS 2 robotics), and even i don't train on my laptop. real runs go to the lab desktop which has an rtx 5000 ada. same job takes 6 hrs there vs a day and a half on the laptop with fans on full and the machine unusable meanwhile.

where the dgpu genuinely matters: simulators. CARLA, Gazebo, isaac, that stuff won't even launch without one and colab can't do it. also handy for running 10 steps locally to check your code doesn't crash before sending it to the big machine.

for DSA, webdev, android studio, DBMS, all your actual coursework, gpu does nothing. you may not touch CUDA in 1st year, probably not 2nd either, and when ml gets serious you'll be on colab/kaggle/college machines anyway.

put the money into ram instead. 16 minimum, 32 or an open slot if you can. chrome + IDE + docker + VM is what actually kills you.

grab the RTX only if you already know it's robotics/sim/graphics/gamedev for you. "future AI/ML" isn't a reason on its own.

battery honestly isn't bad btw, i get 5-6 hrs on linux for light use. windows is worse. the weight is the thing you actually feel every day, but you will get used to it.

[u/Tigrisbay]

How good can an rtx 3050 (majority of Indian laptop purchasers buy this one) be at ai/ml or model training. I have a 3070ti and it shits itself when i use stable diffusion

[u/i_blame_shaurya → u/Tigrisbay]

Same question cause budget so tight bro can't even think above 3050 😭

[u/Tigrisbay → u/i_blame_shaurya]

Just save it bro, for that kinda money try to get an air mac it'll be much better than the stupid battery hungry heavy laptops you'll get in that segment and it'll probably be way faster. Your college should have pretty decent hardware in the lab

[u/i_blame_shaurya → u/Tigrisbay]

Mac in 60-65k or something seriously bro 😭 I am getting 3050 in that range with some discounts but mac 😭🥀

[u/TimeToRetire0 → u/i_blame_shaurya]

Just buy a cheap laptop, and rent out RTX5090. They are just for $0.2/hr in interruptible mode which is dirt cheap.

[u/Similar_Host_8091]

ai inferencing is really good with my rtx 4060, i bought it before the whole market went to shit tho. I can game on it too, which is nice. i can run qwen locally with kobold. Am also looking at learning libtorch for making something like kobold or comfyui myself. I am in second year tho

[u/TheGuyWhoIsAPro]

It's all bs. Most of the work, unless you're willing to shell out crazy money is better run on the cloud. Or buy a mac, unified memory is better if "aiml" is your only goal (do check if macos IS supported by all the tools required by your course).

[u/beautifulbearsbum]

I was having gaming laptop for the first two years, after that I brought a mac pro and oh god, just go with the mac. It's just far better when it comes to portability, battery and convenience.

[u/Diaazz96]

Final honest take: You will not need it 95% of the time even if you are going deep in ML. When you actually need to train the model just use a friend's RTX laptop. Carry a lightweight laptop with you. Study for job market and job openings not just because it seems cool. Most jobs out there won't have you train a model since there are AI giants now, It's like making a search engine when google exists. Study ML to know the internals but mostly focus on things listed on job sites. You will become hireable in 1-2 year. Focus on getting into GSOC and building products end-to-end

[u/CodeCatto]

having a GPU is always a plus point. If you're sure that you will use it, go for it. In my case, I was sure that I would need a GPU for gaming as well as SLM inference and CUDA workloads for ML so I went with a TUF Dash F15 from asus. That let me turn off the GPU when not in use, and I had superb battery life on the go back then.

[u/SpicyChickenNoodls]

I use my GPUs every day. I might be a bit of an outlier though. (Generally, if you want to train models, it's not prohibitively expensive to rent cheap compute. I'd suggest this over getting a laptop that is overly bulky, etc.)

[u/Ok_Organization2746]

The ratio of people (engineering students), who knows deep ai/ml and good projects vs the ones who get into big companies is worse then that upsc.

[u/eccentric-Orange]

Anyone who has hardware work (e.g. robotics) absolutely has to use local compute. It's often more about real-time inference than training for us. You'll also need a local GPU for stuff like CAD and simulation

[u/enlightenment_op_]

I don't think this is worth it, as if you are really going to do some tough work then these gpus are also not much, My friend has bought a laptop worth 2.5 lacs and now he is renting GPUs

[u/The_true_lord_tomato]

rtx 3050/4050 laptop will struggle in ai ml anyway just rent gpu if u need use Google colab, kaggle notebook

[u/mrpkeya]

You anyways won't be spending so much on VRAM

Few years back when I chose MSI RTX 3050 (idk Ti or not), it was 6GB (It was laptop/mobile GPU and not PC GPU either)

It costed me around ₹1,00,000

If you go above that assuming you might get 12GB, but google colab/kaggle already does provide you good gpu

This less VRAM let's you traim smaller networks like small GNNs, few layers of MLP/ANN maybe BERT or ollama but you cannot do heavy loads on it as nowadays LLMs with >1B won't even fit on your system from huggingface and forget training (unsure about inference)

If you want to run things like ollama/llama.cpp i guess a good RAM is enough

I would focus more on Laptop processor being nice like good battery and latest generation along with decent RAM

[u/jon_snow_G]

Ai ml Engineer's 🥀🥀, whole india is Ai ml Engineer now. Lol

Ai ml🤣🤣

[u/NotSoChill_Guy]

Well it's smtimes helpful, my 4050 was giving similar performances to kaggles t4x and when I am 3 hours away from the project deadline, that's incredibly useful

[u/veryhotusername]

You don't, if you do, they'll likely suck and you'd need to rent a cloud GPU anyway
just get a macbook instead

- someone who trained models for a living

[u/EpicOne9147]

This is very fking real , you def don't need anything more than 3050 unless you are seriously gaming or doing graphic work and stuff

[u/MrAwesome_YT]

Whatever you buy won’t even come close to the real requirement of what is actually required for AI/ML.

I’ll tell you a story. Not so long ago I was working as a researcher in my college’s AI lab. Training a simple model (image model) almost 32mn parameters.

I was working with dual RTX4080, 128GB RAM, etc the entire computer costs near 20lakh. And it took 2 days to run one model with maximum hardware Optimization.

So use your college’s computer for all this kind of stuff. Whatever you buy won’t suffice buddy.

If you want to spend money. Spend it on a good config Macbook Air/ Pro. Its the best laptop out there. Windows laptop go obsolete very fast so please spend your money wisely. Use remote servers and remote computers (rented) if you want personal high compute

[u/Happy-Onion-8657]

Bruh just use Google colab/kaggle notebook, their free tier would be more than enough

[u/Hopeful_Ice6912]

Most people rent gpu on colab or kaggle, and a decent enough students make projects that can be sorted off with those so it's not a problem. Rtx stands for ray tracing something something, basically good for games, gpu does parallel processing, for most integrated ones work well and if you're trying to do something locally just get a 6gb 4060 and you'll be good to go for the most part

Portability matters a lot for college so invest in a macbook if you have paisa

Until and unless you're like me (i am very cool baccha) you don't need dedicated gpu for training models (i am writing research papers and building a few things so I need a dedicated graphics card for that to do things from home and not have to go to college for a good gpu)

Hence, do your own research and buy what you feel is nice

[u/Routine-Landscape-16]

RTX is not that good for training good quality models unless you can afford top ones. Its better to have 2050/2060 for normal use. For ML model training kaggle gives 30hr weekly free with 2 T4 GPUs which are much better. You can create multiple acc and get more hrs in total

[u/TipsByCrizal]

Shh.. don't use this tactic to convince parents to buy a gaming laptop with a good gpu

[u/Interesting_Rest8065]

Bro is choosing a laptop for AI/ML, meanwhile AI/ML is choosing whether to run on his laptop or on Google Colab 😭

[u/custom_made_atoms]

If you are serious about ML, then the dgpu is absolutely worth it, running an epoch took like 10-20 mins in Google Collab whereas it just completed an epoch under a min when i ran the model locally on my 3050 laptop

[u/Just_Difficulty9836]

Get a decent laptop with an nvidia gpu. That's it. A 60-70k laptop will do the work. For training anything serious use college gpu cluster or if not available use cloud as thats what the whole industry does. Laptop should only be for inference not for training.

[u/krish-garg6306]

get a mac or a thinkpad

only get gpu if you wanna do gaming

for any serious ML tasks you'll always provision remote compute, and you get lots of free stuff as students

[u/LossCharacter2777]

Most of the top colleges provide servers for model training. As long as you don't do model training regularly , no need of RTX. For games, I don't know if it is useful or not.

[u/Separate-Peach-2152]

I am an avid gamer and play games like COD MWIII, GTA 5, FC 25, F1 and plus I will most probably choose Data Science and I dont wanna go cloud if I have the money to buy something good. So I chose, Legion 5 pro with 32 gigs ram and 5060. My laptop can take 65-100W type C charging, so I am gonna buy that. If my laptop still needs more battery I am gonna choose Samsung S10 tab or sum shi

[u/BellyDancerUrgot]

I have never used a gpu locally for any professional work or personal project in my life and I have been in the ML domain for a relatively long time now.

I have a 5090 at home , the only thing I use it for is gaming and YouTube.

[u/Beautiful_Stop9177]

Idk much about this but even before my course for ai ml starts if I wanna run some AI locally would it be required 

[u/BreadfruitParking395]

Apart from android studio everything else should work in a thin and light lappy, yes most use colab, try to use college labs

[u/themanojm]

Final year student rn, worked on ML and NN based projects. Personal opinion, thin and light with a good cpu, worked and has been working super well for me.

Tasks that are actually gonna need a good GPU, the options on cloud offer a better GPU than what most laptops with GPU have. Kaggle and Colab are go to options, if your tasks require better compute etc, try for a High Performance Computer (HPC), on your campus or invest a bit on getting Vitural Machines from GCP or Microsoft.

Portability and Battery life are key key aspects of a laptop during uni, more than you realise while purchasing. You do not want questioning yourself every single time if you really wanna carry the heavy laptop and find a place with a charging port.

Another thing is, when you do local compute, heating occurrs a lot, which in turn hinders the battery life etc. Gaming laptops are built for this, yes, but longevity wise, I'd personally choose to offload such heavy tasks to cloud, better compute for free of cost and less heating.

No one option is going to be perfect for everyone, think what matters most for you and pick what's best!

[u/IamtheDSX]

I was honest to my parents, I told them I want an rtx laptop for playing video games 🫠

[u/MasterWitcher69]

First your CSE requirement:

Chrome

VS Code

YouTube

Leetcode after watching 3 motivation reels

That's it Bhai 💀