RAM

Sharlach

Another beautiful mind from the Reddit brain trust, I see. Legally binding agreements to purchase memory in the future are not "manipulation." That's the actual business, selling RAM.

GAV17

This is not a cycle or the beginning of a new one, because what's happening with RAM prices is unprecedented.

GAV17

The only possible bubble is in the prices of components for datacenters. The balance sheet of $MU is fantastic, but it needs the RAM prices to remain astronomically high (which is a possibility). It would be like looking at $XOM's balance sheet and it's valuation if oil was at $300. It looks great today, but how is it going to look in 5 years.

starf05

RAM producers are printing money. They will easily be the most profitable companies in the planet this year. 

highchillerdeluxe

People screaming that RAM is cyclic probably have an aneurism by now.

TequilaTrader

If it was for RAM coming out of the gutter for me this week I’d be depressed.

TequilaTrader

Anyone have DRAM OR RAM?

TequilaTrader

Almost sold my RAM at a loss today cause I was getting crushed. Fortunately I said F it.

fartpooppee420

Is 4gb of RAM with my laptop enough to make sick dubstep on FruityLoops

Sharlach

Not sure how much lower these PE ratios have to get and for how long before everyone realizes this RAM shortage isn't ending for years, but another quarter or two like this and they'll be at 1:1 😂

BatMore6724

Do the results + potential 10 year LTA and musks comment on how robotics will consume all RAM prove that memory isn’t the same boom and bust cyclical sector anymore? Buy DRAM and hold long term?

TequilaTrader

I’ll pray for you. I have RAM so that would help me doubly

mschuster91

You realize that you can self-host models? And that TSMC is not American but Taiwanese, and that TSMC is building capacity in Europe as well? And that Samsung, which is Korean, also has AI compute capabilities in their Exynos chipsets? There is **no** fundamental American moat anywhere in the AI ecosystem. The only moat is in the hands of OpenAI because Sam Altman singlehandedly wrecked the RAM market... and that will vanish in a few years.

coconutts19

idgaf as long as they buy more RAM

mightyblend

Alas, I did not buy a few years ago. (Actually, I did buy a ton of RAM tickers before anyone else seemed to think about it, but then had a personal emergency where I had to sell and I am, uh, very angry now.)

burnerdadsrule

Also these GPUs are not 1 time costs. They need to be replaced every 1-2 years. As GPUs and RAM get more and more expensive because NVidia is practically forcing they're clients to buy more than they need.

PeachScary413

It's because they managed to capture the market and locked it down, what you are seeing is the effect of a monopoly (or maybe oligopoly) on the hardware market. Both the GPU and the RAM makers realise that it's more profitable to strangle production and sell at a massive premium instead of increasing production which would be costly and risky (and ultimately cut into their profit margins).

MimsyWereTheBorogove

CapEX depreciation. and perhaps even fraud on that subject this is going to be the core of the AI bubble popping first thing to know is that the GPUs they are buying can be depreciated over 6 years. secondly, that they only last one year when being used at 100% 24/7 they estimate that most of their GPUs are usually running at 50%, so we can give them the benefit of the doubt and say they last 2 years. third, they have been buying and warehousing the GPUs to get ahead of it and make use of the capital investors have given them fourth, the warehoused GPUs will likely be obsolete by the time they are used because of how fast the advancements are being made All of this applies before you decide to put data centers in space, I would ask you if you think a highly sensitive machine can survive a rocket ride (They cant), and if it's cheaper to cool them in space with radiation (it's not) and if its easier to replace the GPU's in space (it's not) and if they last longer (they dont) Chip makers are a buy, they will keep buying them and throwing them in the trash. The prices of used and obsolete GPUs and DDR5 RAM will crash as a result of the abundance When they finally are honest about the depreciation and how many they are burning through... the investors will have to be honest about the business model. And the P/E ratio will skyrocket because ... My $20 AI subscription, costs the seller of that subscription over $80/month in electricity, land, and hardware I cant say for sure, because i'm sure their lawyers have done a good job of keeping it legally grey... But this is Enron level stuff

CheesecakeCandid3635

Musk said robotics will use up all the RAM - memory not cyclica anymore and good for long term hold???

Ok_Cry7572

Elon might hate neoclouds but he seems to love memory 😂 “Robot RAM needs will exceed everything else on Earth.”

Aggravating-Good4879

RAM is the 2x DRAM etf so deffo FULL PORT AHEAD

Ok_Cry7572

It's interesting that Elon keeps referring to RAM, not DRAM. Anyone here know why?

Sure_Let6170

Yippi-ka-yay. Even the fucking shittiest RAM manufacturer from korean backwater is up 500%, but you got your 90% from prime AI hyperscaler company that actually started the whole fucking AI race. What a humble person you are. Wanna switch to boomer stocks? They would suit this mentality.

Oorangootang

Sure I'll look forward for you. Labor doesn't need metals that are being tariffed and are a finite resource that will only ever get more expensive over time. Robots require processing, RAM, and other expensive electronics. They require *actual* power which is already getting eaten by AI, and they require maintenance so you still can't completely eliminate labor from the equation. Oh, and they are a depreciating asset that can't be easily replaced.

jjwhitaker

If you have the hardware a local model makes sense and will offer you a lot of functionality. It's able to save on cloud credits or take over smaller work items entirely. And it's only getting better. Qwen 4.0 Flash Next is on the horizon. If it can sit on a 128gb RAM system then I don't see me using cloud AI tools at home.

Independent_Band59

I thought Micron was president of France. And protests were about RAM prices

pbeenjoyer555

I can't help but laugh that while I can't afford RAM for a new PC, these people are legit putting their live savings into a bunch of buildings that will become unusable months after being built when the crash happens.

Gorgenapper

Holy fuck the prices of RAM at the store are insane.

juuular

I’ll let gemini explain it for you: No, quantum computing is not a suitable or practical solution for the KV cache VRAM scaling problem. While it is easy to assume that quantum computers can fix any "hard" computational bottleneck, the KV cache bottleneck is fundamentally a memory storage and data movement problem, whereas quantum computers excel exclusively at specific algorithmic math problems. Using a quantum computer to solve KV cache scaling misalignments comes down to a few fundamental architectural mismatches: 1. The "I/O Bottleneck" and Quantum Memory limits The KV cache scales linearly because it physically stores millions of high-dimensional vectors (floating-point numbers) representing past tokens. [1] (https://rajatpandit.com/ai-infrastructure/hierarchical-kv-caching-vram-limits/), [2] (https://lyceum.technology/magazine/kv-cache-memory-calculation-llm/) • The Problem: Quantum computers have incredibly small registers of qubits. Even advanced quantum roadmaps deal with thousands of physical/logical qubits, whereas a heavy LLM KV cache requires hundreds of gigabytes (billions of bits) of active memory. [1] (https://aerospike.com/blog/kv-cache-tiering-gpu-memory-limits/), [2] (https://www.youtube.com/watch?v=BcbPMKWqtUc) • The Input/Output Wall: Getting classical data (the LLM's activations) into a quantum state (Quantum RAM or QRAM) and reading the results back out introduces a massive bottleneck. The time spent translating classical data into quantum states would entirely destroy the speed benefits of the cache. 2. Linear Storage vs. Exponential Speedups Quantum computing is powerful because it can use superposition to explore an exponential number of possibilities at once (e.g., Shor's Algorithm for factoring or Grover's Algorithm for database searches). • The KV cache is a retrieval lookup table. It doesn't require exploring hidden pathways or solving highly complex mathematical equations; it simply requires the GPU to quickly read previously computed vectors out of high-bandwidth memory (HBM). [1] (https://www.linkedin.com/posts/v2solutions_llm-aiinfrastructure-mlops-activity-7452348061080682496-_RIh), [2] (https://www.youtube.com/watch?v=BcbPMKWqtUc), [3] (https://aerospike.com/blog/kv-cache-tiering-gpu-memory-limits/) • A classical digital memory chip is already optimized for this. A quantum computer provides no algorithmic advantage for simply holding onto linear data arrays. 3. The Real-World Solutions Being Deployed Instead Instead of looking toward quantum mechanics, the industry is solving the KV cache "VRAM Wall" through aggressive classical hardware and software engineering: • Hardware Tiering: Shifting "cold" parts of a conversation's memory from fast GPU HBM down to cheaper system CPU RAM or ultra-fast local NVMe SSDs. • Extreme Compression: Utilizing deep quantization techniques like Google's TurboQuant (released in 2026), which compresses KV cache tensors down to 3-bit or FP8 precisions, squeezing 4× to 6× more context into the exact same GPU VRAM. • Architectural Shifts: Moving away from Multi-Head Attention (MHA) toward Grouped-Query Attention (GQA) or Multi-head Latent Attention (MLA), which naturally reduce the physical footprint of the KV cache by 8× to 14× during the model's training phase. [1] (https://www.reddit.com/r/LocalLLaMA/comments/1s2su28/google_research_turboquant_redefining_ai/), [2] (https://medium.com/@adityaj5400/the-kv-cache-is-killing-your-llm-at-scale-heres-the-low-level-physics-nobody-talks-about-b577c4c7549e), [3] (https://www.youtube.com/shorts/rmTXNROsSQg), [4] (https://aerospike.com/blog/kv-cache-tiering-gpu-memory-limits/), [5] (https://rajatpandit.com/ai-infrastructure/hierarchical-kv-caching-vram-limits/) Are you exploring this from a hardware architecture perspective (trying to understand future hardware bottlenecks) or an infrastructure deployment perspective (trying to host a model right now)? If you are hosting a model, let me know your hardware setup, and I can recommend the exact classical optimizations (like vLLM or TurboQuant settings) to bypass the VRAM limit. [1] (https://introl.com/blog/kv-cache-optimization-memory-efficiency-production-llms-guide), [2] (https://medium.com/@adityaj5400/the-kv-cache-is-killing-your-llm-at-scale-heres-the-low-level-physics-nobody-talks-about-b577c4c7549e)

pkhairnar6

There is a meaningful moat to specialization in custom chip design combined with the infra around it. That will give them bargaining power which Micron will not have once the RAM boom ends.

Vlisa

market=/=economy clouds can keep debt spending for awhile regardless of stock price. Not to mention plenty of other buyers of RAM waiting their turn.

bluen

I need some cheap RAM

BuyMeaSalad

Is that open source tho? Like you need the hardware to run it? Something interesting I don’t see people bringing up are the Nvidia Spark laptops/desktops. If the future does end up going open source on local hardware, won’t demand for RAM/CPU/GPUs still exist just on the personal hardware side? It seems like Nvidia is preparing for that by offering a product that can run local models

bluen

Bruhs you can get RAM adapters to convert laptop ram into pc ram

ferrari-g-91

Cheaper RAM only helps if weaker spending doesn't delay upgrades; a bubble unwind could hit both Apple's input costs and its buyers.

imacyco

Right, all sounds good on paper but it doesn't happen in an instant. Right now we're seeing stuff bid up month over month... You can see that in RAM and GPU pricing creeping up over time. When it stabilizes, and there's a new equilibrium point between supply and demand, if both hold, you'll see inflation come down. I think prices have kind of stabilized month over month, but inflation is measured year over year.

EmergencyRace7158

35% of semiconductor orders are from neoclouds. If they're out of the picture it's not just a disaster for the semis but they'll lose pricing power and the hyperscalers plus spacex will be able to pick up all those CPUs, GPUs and RAM chips the neoclouds can't pay for cheaply.

MikeCheck_CE

October 15, 2026, Elon Musk posted on X that "China will be making a LOT of RAM in 2028," (Then follow up later with: Micron has been “reasonable regarding future memory prices, while others have been extortionate") - in other words he got what he needed from Micron now.

fuckitdawgimhungry

apple spends 10s of billions per year on RAM wuts ya point

felixthecatmeow

Another aspect outside of just GPUs is AI training and inference is orders of magnitude more compute heavy than the vast majority of other cloud workloads. I'm a backend software engineer at a tech company that's top 20 in web traffic and our whole company's infrastructure outside of AI/ML workloads could run out of a single data center easily (disregarding issues with geographical latency and single point of failure). My team owns some services that handle billions of requests per day and collectively run on less than 100 CPU cores and 200GB of RAM. That's basically a single server and likely some headroom left on it for a scale that the vast majority of companies will never reach. Comparing that to AI, I ran some video generation models a while back and had a server with 128GB RAM and a 5090 and it would take minutes to generate a single 7 seconds video. Prior to AI the big 3 cloud providers weren't struggling to meet demand because while it was growing a lot, it was doing so at a rate that they could easily match because building a few new data centers would add a ton of capacity. So if AI demand suddenly fell off dramatically, I don't know if it would even be worth repurposing a lot of these DCs, unless there's new demand for a different type of compute heavy workload. All that to say it's not just NVDA. RAM demand and prices are through the roof, and companies like MU have seen their stock skyrocket. Same with high speed storage / SSDs.

bluen

bruhs im about to embark on a journey of deep research into RAM

The_Macro_Investor

If you’re truly bored, you can make your own RAM: https://www.tomshardware.com/pc-components/dram/dr-semiconductor-successfully-fabs-ram-in-garden-shed-cleanroom-array-of-memory-cells-with-12pf-capacitance-groundwork-for-much-larger-future-array

Samjabr

Poor people won't riot if they can't eat RAM

WorthAd9397

So the DOJ and state AGs filed antitrust lawsuit against egg producers for pricing fixing during egg shortage. Why the fuck don't they do the same for RAM?

abandoned_idol

How do I change them? The companies don't change. I still have the same amount of capital. I can't really benefit from changing anything today. I put my capital in for the long term on smart companies. I'm staying away from RAM companies, too scary.

artbystorms

Hopefully. I'd like to be able to afford RAM, storage, and GPUs again.

ggRavingGamer

Idk, all I know is that Gemini put some heavy usage limits on. Like, 5-6 prompts with the medium model, takes about 50 percent of a 5 hour usage. That's nuts. So I suspect people are realizing it's really that unprofitable. At some point it's gonna get bad. We're gonna have RAM again, but are going to be jobless, friendless, dickless cause the whole economy is gonna crash hard like a junkie at 3 AM.

buyatollah_kuminamy

Anyone rec o good gaming laptop under $1000? Gotta be 16G or RAM with Gforce

phylean

This is assuming costs are not coming down eventually as well. More GPU, RAM, servers, etc. needs are met over time which reduces costs. Eventually infrastructure costs will come down to prices that are similar to what they are selling the subscriptions for. This happens to all technology. Just look at stuff like (mobile) internet, phone plans, web storage, even compute and electricity

SirBuysHighALott

He is though. Have you seen RAM prices and HD prices for normal consumers?

BladeFireQ

The RAM prices are absolutely worth it 🥀

PassableForAWombat

Yes but you’ll experience RAM speeds from 2000

bluen

bruhs can we attach a USB dongle to connect some external RAM? 🤔

hammertiming_

Not necessarily. With somewhat modest hardware you can do decent things. I've got an M1 Pro, which is already 5 years old, and it can run local models. And local models will keep getting better and requiring less CPU/GPU/RAM to run. As I said, I don't think there's an scenario in which AI companies make money on a big scale

MacaronNo5646

I for one look forward to be able to afford RAM again

lasooch

I’m not saying The Poppening will give you a cheap 5090. The AI chips are useless for vidya, so even if the hyperscalers and neoclouds resell them instead of just burninating them, you won’t get to play GTA 6. I’m saying they’ve sucked up all the production capacity of GPUs and RAM just so that they can buy hundreds of billions worth of warehouse decoration. Including production capacity that coulda gone into your PS5.

Pale-Silver-8178

Can RAM become cheaper now guys

PaulaPaulaPaulaa

Fuck AI let us buy affordable RAM

Olangotang

> shit half of this bubble seems manufactured by the hyperscalers to shit on local computing, which it has. That's more in OpenAI and Anthropic who bought up all the RAM to secure a temporary most. They starved their competition.

gayteemo

speaking of which, if the AI boom is over it means prices on RAM will finally come down as well which will be good for apple. shit half of this bubble seems manufactured by the hyperscalers to shit on local computing, which it has. but really i think this is all just about apple being the only big player in tech who isn't massively reliant on ai capex

Fit_Neighborhood9251

RAM is 50% off ATH, Cables are 50% off ATH, almost every memory is 40% off ATH, Datacenters are 40+% off ATH and there are still people here screaming for AI bubble.

FUCKYOUINYOURFACE

My M4 Mac Studio with 128GB of RAM was one of my best decisions!

BFox1982

They're eating the chips. They're eating the RAM.

pragmojo

Don't get me wrong, I'm long Apple, but I do not know how they are going to navigate the RAM shortage (i.e. all consumer electronics doubling in price)

PaulaPaulaPaulaa

fuck AI, slop is the reason RAM is so high

iamthe0ther0ne

Why do you prefer Strata over Ollama?  Doesn't using Ollama also let you leverage their open weight cloud models?,I only have 32 GB RAM and need all of it for work programs (including Claude).

nunununuhu

In six months or a year any of a dozen competitors will be at parity of Claude Opus. I keep saying this and no one is listening. But it's all one clever math paper away from obliteration. There's nothing that says you can't run the latest and largest models on a regular laptop with enough RAM. A speech transcription model was released on October 19 - it has a word-error-rate of 11%. It runs at 500x real-time speed on my laptop. The state of the art in 2022 was 7% WER with the Whisper tiny model, which is a 40 million parameter model running at barely 5x real-speed. That is to say: speech recognition models have shrunk about 50 times in size and improved 100 times on inference speed. With nearly the same quality. All deep learning models are subject to this kind of compression. It's an open question in computer science what the inherent entropy of an AI model is - how much information is required to represent the emergent property of intelligence inside the model? It's not actually trillions of bytes. It doesn't actually require the entire matrix be "stirred" constantly. That's just a limitation of our current approach and it's not an inherent limit from information theory.

EngRookie

1) i literally said i was joking around with you. 2) if you want real advice stop trading options. That's it. Start investing in index funds and put away at least 15% of your income into retirement. If you find that too boring then invest in companies with strong fundamentals, the companies i invested in i researched heavily and invested in them when i believed they were undervalued and i never invested more than i was willing to lose so i could hold through downturns. I started buying AMD in 2020 and kept buying even though everyone shit on them did the same with INTC and averaged down from $43 to $23 and bought shares like crazy as it was near book value under $20. Currently holding NTDOY at (13%) as i believe they are severely undervalued and still being evaluated primarily on cyclical hardware sales(with RAM costs being overblown on future earnings) instead of an IP driven entertainment company. I have invested in many other individual companies too and done well but a lot of that is luck enetering the bull market early but I also saw that the drawdown during covid and the yen carry trade was overblown and invested a good chunk of my dry powder. Which netted me massive returns on my risk. bottom line dont trade options, it is just gambling with extra steps. Index funds over 40 years of investing will get you a decent nest egg but you can boost that with key picks in individual companies. And while i dont agree with margin or leveraged ETFs it can help, in short term bursts, help you greatly outperform the market during bull runs. be prepared to do actual research into companies and read a lot of earnings reports and projections, it will help you tell the difference between momentum and actual value. Good luck, and God Bless Canada and God bless Ryan Reynolds

gayteemo

surely raising the prices of RAM infinitely while never increasing supply is sustainable

SailingTheInternet

My RAM position rn https://preview.redd.it/cje6rkk60uwh1.jpeg?width=1320&format=pjpg&auto=webp&s=24d7c97ce989df30426808afe98055b0cfab45a3

Individual-Round2767

Not 100k but i have 3k in SOXL 3k in RAM and 9k in DRAM

nicolas_06

What I can tell you is we migrated to the cloud and our expenses sky rocketed. Our datacenter was amortized and mature. We have say about 10 thousand VM overall. A few years back it was like 56 cores, 256GB RAM type of machines.

spellbadgrammargood

First they came for the Neoclouds but I invested in the neoclouds Next they came for the RAM but I invested in RAM Then they came for the data centers but I invested in the data centers Then they came for GPUs—and there was no money left for me

TitaniumSand88

Been stocking up on batteries in case it’s the next thing to have a supply shortage like RAM. I have a lot of AA and AAA batteries.

visionarymind

Lemme see your D>!RAM!< 😏

good-times-

What kind of RAM u drive?

-Crash_Override-

It won't make one shred of difference. Google has a huge equity stake in Anthropic. and is continuing to pour money into it. They're tied at the hip on the ledger as well: >In the first quarter of 2026, Alphabet reported net income of 62.6 billion dollars. ..... More than half of that profit, roughly 37 billion dollars, came from net unrealized gains on non-marketable equity securities. The biggest contributors were Alphabet’s stakes in SpaceX and Anthropic. There is also the massive TPU/Inference deals that OAI has with Google Cloud. So Google would be fkd 3 ways to sunday... 1. Their P&L is dependent on the the compute that AI companies use. 2. They have placed large bets on Anthropic thru equity stake and future commitments. 3. Any catalyst that would cause AI to crumble would also cause Gemini to crumble. Honestly, I'm shocked that this sub of all places thinks that AI exists in any semblance of isolation. And that if it were to 'pop' that consumer RAM prices would come down and everyone would be happy as a clam.

CommercialHour6660

Yup. More completely, the oligarch funded frontier labs starved all the nimble Western competition from hardware. US would have competition beating out China but they've all been stamped out by big tech.  This doesn't affect China because they make their own.  US big tech needs to be broken up. Buying up 3 years of the world's RAM production to stifle potential rivals is absurdly illegal. Antitrust. 

Olangotang

China won because the Frontier Labs starved everyone else out of RAM, and China has to improvise with lower powered hardware.

Olangotang

I'm just tired of telling me how fucking magical LLMs are white I use open source models that let me do whatever the fuck I want. Frontier Labs are a scam, and they bought up all the RAM for a temporary moat. I hate how even being pro AI but against the circlejerk means you're a "luddite". Working with vibe coders is pure fucking torture and that doesn't stop until the bull comes due for management lol.

Wonderful-Sail-1126

99% of people can't run local LLMs. It'll burn their laptop, even if they have a decent Mac. Not only that, something like ChatGPT is free and ad-supported. 99% of people will find it far more viable than downloading LM Studio, look for a model that fits my computer's RAM and GPU, add in MCPs like search, photo analysis, memory, etc. Local LLMs that can run on these crappy Windows laptops are insanely slow and bad.

CommercialHour6660

To me the interesting part is China.  US oligarchs were running the well worn Silicon Valley monopoly playbook. Pick a few winners early. Make sure the good olde boys have all their cash in. Use vast weath (not innovation) to get years ahead of the competition. Then shut everyone else out via regulatory capture and monopoly practices.  You can see their different approaches play out. Buy up all the ram for the next 3 years of production. Buy up all the chips. Fearmonger about Gyna and pretend you care about "responsible safe AI" while your agents commit dozens of felonies. Lock down your apis so they're barely usable to protect the IP you stole.  The problem is that China isn't playing ball. South Korean Chaebols will gladly price fix for you and lock your competitors out of the market for a fee. Europe is, no offense, still the US's bitch boy and won't dare build competing industry. China said nah fuck that we'll just make our own RAM and AI chips and models with open weights and hookers and blow.  You're seeing the US tech monopoly that been run by the same broligarchs for decades unravel. Caused ironically by a free market nation like US was once. For the first time the winners weren't chosen in a Signal chat with Musk, Thiel, Sand Hill Rd and the Paypal Mafia. China won't collude with them or stamp out the competition because they want their own AI industry. And China is the king of commodities. Their whole angle is using their vast free market to destroy entrenched inefficient monopolies.  Every time China releases a free model the collapse of US oligarchy comes closer. The latest DeepSeek is as good as Opus 4.7 for 1% of the price. US broligarchs invested in scale instead of model efficiency and now Gyna is out innovating them.  Honestly fuck em. OpenAI and Anthropic were planning for decades of price gouging. The typical you'll own nothing and be happy. They were even talking about everyone having "subscriptions for intelligence". Now we're a few years away from having Claude at home. Running on Chinese hardware they can't gatekeep in their datacenters. 

jeffroeast

Problem with that is those smaller companies won’t be able to compete with the big dogs who buy up all the GPUs. Nor will they be able to absorb the higher cost of CPU/RAM/Storage, which are also skyrocketing due to demand. Preference for available stock will always go to those with the most $. There is literally no stock even for them to buy for the next couple years. Smaller companies will get 0.

canxkoz

Check RAM and DRAM

tano-01

It kind of is. Just like the deepseek drop, CXMT suddenly announces that they’re going to produce RAM and so semiconductors routed. But there’s other factors as well. Interest rates / bond yields. AI company profits and their borrowing. Inflation. High tech valuations. The rest of the economy. But build out is continuing… Yes. Lots of earnings reports starting this week so let’s see what happens. I’ll be watching a few closely, META, Google, Hynix, WDC, SNDK, MSFT. I’m hoping for a rebound. Not sure if this is the end just yet. End of November NVDA reports.

Kickboy21

Thanks for the rundown. I think ill stick with pro and 24 GB RAM 1 TB STORAGE but not sure on 14 vs 16 inch. Ill have to get a feel of it in person at the store

The_Macro_Investor

Last of Us 2 Remastered (which I used to get the most intensive specs) and RDR2 are not Mac native, so you’ll need to get the equivalent of Rosetta Stone which was a windows emulator for the Intel Macs back in the day.  I haven’t kept up with the M-series emulators.  Otherwise current MacBook Pro Models should be more than enough to run those games. I weighed looking at the MacBook Air models for you but I think (and correct me if I’m wrong) you want to prioritize longevity over cost and weight.  Supposedly the difference between an Air and a Pro is the fan, but heat buildup can age things quickly, and you’re running games which is more graphic intensive. The 16 inch model takes you right up to $2,999, but it includes the M5 Pro chip as stock, with 24 GB RAM and 1 TB storage, so if you can go a bit over budget for sales tax that might be a good choice. The 14 inch model gives you more flexibility.  You can choose between an upgrade between the processor, RAM, storage, or the nano textured screen, or maybe two if you tweak the numbers around a bit and still be under budget.  Keep in mind if you choose to customize it won’t be available stock in store and you will either need to ship to store or to your place of residence, which will take time. There may be a recycling fee depending on where you live, so you may need to factor that into your budget as well.

Intelligent_Tie_1109

Cyclical always look cheap at the top of a cycle. Semiconductors are notoriously known for this trap. What your missing is the massive amount of chips and RAM that will hit the market by 2028-2030. Pricing a company like MU even 2 years out is difficult

Vlisa

RAM prices going to be cut in half by next week :dance:

SoulMute

How’d you know China was gonna announce Chinese RAM?

Arnab_Goswami_RTV

Can I get cheaper RAM already

ResidualSodium

Because it’s artificial. In that, RAM, GPUs, and other components are being set aside to get these data centers up and running. Also, see RAM producer collusion. I honestly wouldn’t be surprised if in 2 years we had an equivalent of ASIC chips for AI, making the GPUs NVDA is making currently obsolete before their contracts with these centers are up.

ShowerDear1695

Because Loudon built em when RAM prices were low 😒

moorhound

Alright, I'm a little buzzed, pretty high, and bearin the fuck out. There is an actual fucking apocalypse on the brink in the AI sector. The entire lynchpin of this thing relies of AI inference being hardware-intensive; it's why NVDA popped, it's why neoclouds popped, it's why SOXL popped. It's why power transformers, nuclear, glassware, copper mining, photonics, and every nook and cranny of the AI rally has happed. The *entire underpinning* of this AI boom is that this magic thinking machine requires a lot of stuff to make it happen. Samsung Littlebit destroyed all of that. It an AI weight quantization technique that decimates - in a literal sense - the RAM requirements for model weights to function, while retaining most of the model's quality. There's other AI compression techniques that LittleBit can be combined with. It's gonna be the thing, technology demands it. Samsung even released the paper and technique for free, under a non-commercial open license. It might shape up to be one of the most pivotal actions in human history; they made native, locally-hostes personal AI accessable to the common man. But it absolutely *fucks* the AI industry. Every company went full-steam to gain an edge on a frontier market, and they all did it with the same thing in mind; local inference was so resource-intensive that it was unfeasible, it required too much RAM to run on a phone or single computer. The cloud model was the only reasonable way to do it, so they went along with what that requires., which is $750 billion dollars worth of capex to build the datacenters to process all this shit and beam it to everybody. Littlebit2 combined with compatible AI optimization tech like TurboQuant (KV cache compressor) allows formidable models to be ran or hardware people can buy. It's a panacea to the RAM shortage; after QAT, it'll shrink memory requirements of shit like Kimi K3 (2.8T parameter) from 1.4TB of HBM RAM to as low as 200GB of *DDR RAM*. 16B models could be shrunk down to run comfortably on most midrange+ phones. It is just too fucking good not to take off. Samsung published the first study results [back in February](https://arxiv.org/abs/2506.13771), but it just started making Korean circles last week, it's why their institutionals have been dumping ass. Anybody with the compute and the knowhow can run QAT on open-weight models; Chinese models will probably be rolling out with these by November. OpenAI, Anthropic, and all the other fuckos were so focused on the threat of someone else achieving anything closer to AGI-focused high inference that they didn't consider the threat of optimization towards functional inference; no one needs the AI in their roomba to solve millennium problems, they just need it to do its job, which lower weight focused models are efficient at. US AI companies will copy the formula, but they're married to this datacenter buildout and all of the debt it entails. Dropping damn near a trillion dollars into what's essentially pooling RAM, and then finding out you need way less RAM, isn't an option when the contracts are already signed and the concrete is already poured. Besides server-side AI, there *is no other need* for this much compute, we were talking about doubling the US power grid for this shit. We'll still need a lot of it for training, but everyone's been racking debt under r the premise that inference would take even more. Everyone stuck in that $750B investment will have a depreciated asset. CRWV will go to zero, a lot of their debt is collateralized on their GPU racks and if they depreciate past amortization rate their creditors can call in the debt at-will, so it will be torn literally to pieces. Don't get me wrong, I'm extremely hyped for this tech. It takes the idea of the thinking machine away from the monopolistic grasp of sociopaths like Altman, Zuck, etc and allows almost everybody to have their own personal, private, non-subscription, ad-free, auxiliary brain. But for the love of God cowboy, *hedge your fucking shit*. The shitstorm is coming, randy. The shitbirds are up there, flying around, ready to take a big old shit. Especially on CRWV.

moorhound

All the normies gone, and it's just the weekend weirdos left? Ok ^the reason Korea is dumping bags is because of Samsung Littlebit. Drastically lowering the hardware bar for inference means major demand destruction on RAM and the datacenter-based cloud approach as a whole. If people can run 70b models on $10k Mac Pros and 14b models on Huawei phones, no one needs $750bn worth of datacenters we're in the middle of building.

Harp-Note

Does the RAM shortage mean I can sell sheep at higher prices? 🤔

Paul_Robert_

Alleyways in the 2010s: "Psst, hey bro, wanna buy some drugs?" Alleyways now: "Psst, hey bro, wanna buy some RAM?"

Lwl0905

Leveraged RAM

Pan_cake_man

The stock was beat down based on AI fears (basically AI will make video games better than game companies and rising RAM prices. I’m basing part of my thesis just on the idea that those two fears are temporary. Even in the case of higher RAM prices Nintendo is better equipped to handle it than other console manufacturers just for the fact that the Switch 2 only has 12GB of RAM compared to 16GB for the Xbox and PlayStation. Switch 2 was also the fastest selling game console in Nintendo history in its first year and the stock has dropped over 30% since the Switch 2 launch. Eventually console sales will equal game sales. Pokepedia was a huge success for them and Ocarina of Time remake will also be a huge launch for them. They have a lot of cash, little debt, and pay a fair dividend. I’ll just collect my dividend, wait, and ride out the Switch 2 console cycle.

Glum_Spring7162

thank god i bought a RAM when people were saying to buy DRAM