Historical memory prices 1960-2026

> I'm not sure it's right to label vacuum tubes and core memory as "DRAM" though. Core memory does need a refresh after a read, but since it doesn't need refreshing otherwise, I'd mark it as SRAM. Williams tube memories seem DRAM like enough to me though.

The problem with "price per typical-sized RAM chip as sold at the time" is not so much that it's subjective, but you'd get artificial spikes in the data. For me, the key take home from the graph as stands is that price per GB right now is about the same as 2020. That seems reasonable, it's more expensive than it was, but only outrageous if you forget what it was like only a short while ago. But back in 2020, 4GB or 8GB sticks were most common, a few years ago it was up to 8GB, 16GB or 32GB, and now 2x8GB seems to be the most common high-end configuration or 2x4GB for low-end again. If you'd jumped from 8GB sticks to 32GB sticks and back again, it would seem like there was a spike up around 2021-2 and that memory was cheaper now than a few years ago. I think the main driver for the data is that probably consumers or the market decides on a reasonable price for memory, and people buy whatever they can get for that money. When I had a Z80 computer in the mid 80s, 64KB expansion RAM was about £100. For a similar computer but a few years earlier, a 32KB expansion RAM was about the same price. When I had an Amiga in the early 90s, a 512KB expansion RAM was again around the same price. In the 2000s, a couple of MB was around the same price. Maybe 5 years ago, the market was split a bit and a 4GB RAM was around £60 and 8GB around £120, but maybe this reflects "under $100" as the ideal target. A few years ago, it was similar but 8GB for around £80 and 16GB for around £160, now it's "doubled" in price, it's just back to 8GB for £120 again. But whatever the decade, it seems people are prepared to spend about £100 on memory for an average PC.

Depressing to see how much discussion on HN (!!) has resulted from a objectively terrible graph reading. I mean... in the process of our infiltration by finance bros and VC money, have we genuinely forgotten how exponentials work?

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If what you're interested in is fluctuations in production versus demand then you absolutely do not want a subjective metric. Measures of the form dollars per unit, units per watt, units per flop, etc are what you're interested in.

Have you ever actually tried using Windows 10 with 1GB of RAM? I wouldn't consider it suitable for "standard computing tasks." And that's the hangup, what do you consider a "standard computing task?" On what OS? Running what software? How well? Plenty of people were still using XP in 2009, so is 256 MB of RAM okay for "standard computing tasks" in 2009?

That's just as wrong in the opposite direction, y2k was a thing because two bytes were worth the saving in 1980, and we really needed those two bytes.

I still don't get where all that memory goes.

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So total system cost per unit of memory is going up.. 2GB costs in 1985 was $2 million (from the graph), a cray-2 was $16 million (from wikipedia). A GPU server with 8xB200 today can be had for ~$500k (estimate), 1.5TB memory is $25k (from the graph).

The natural unit of measure for integrated circuits is a power of 2 since that's what the systems operate in. It's so natural that early 9 and 36 bit architectures were squeezed into 8 and 32 bits as it just works so much more efficiently. Long term storage and communications? Those start to introduce things like human division of timings, frequencies, and other analog systems like rotating disks. It still generally makes sense fab actual flash chips in various powers of 2 though. The discrepancy there tends to be various forms of 'overhead' for the translation table / wear level indirection, over-provisioning, and even variations in density caused by different levels of physical cell utilization. Still, most network stuff ships around packets of 'up to' 1500 bytes ( https://en.wikipedia.org/wiki/Ethernet_frame and lets just exclude jumbo frames ) so arguably it'd be better to talk about all computer measures in binary powers of two, exclude the marketing huckster trying to make things more impressive by shoehorning SI engineering units into a realm that uses binary math.

How do you explain this discrepancy? Is it because the OS is agressively fencing in and pruning these wasteful software?

Second-hand? lol my main driver has 16gb and just peachy. What do you folks do that needs so much ram to browse the web.

My laptop has 8 GB. I write blog posts, I have a dozen-ish tabs open, I do KiCAD things (including 3D renders!). Works great. I was doing Verilog synthesis on a similar machine in college in 2020. The truth is that, if you do the same things you were doing with your computer 10 years ago, well then you don't need a new computer! If all you do is write books, a Pentium III will do the job just as well as a brand new PC. Of course, the web throws a wrench in this. Word 2003 is still far more capable than Google Docs, yet tons of people opt for the cloud slop because it's convenient and free-as-in-beer. And, Google Docs will continue to become less efficient with time.

> only visit certain websites that can be visited on older version of browsers. A second-hand 16GB laptop can go a long way. My desktop has 8 and I have no problem keeping multiple tabs open using up-to-date Firefox.

You can do a lot on old machines but developers also need to optimize a bit. Youtube almost plays on a 20-year-old machine, which means with some effort it'll play just fine. Most the other sites work just fine.

They weren't though when you adjust for inflation. If you took inflation into account, ram is cheaper now by $0.89/GB for DRAM compared to 2012.

Moore's law is about transistors doubling every interval¹ *on the most economical package*. Wikipedia is misquoting it, and extraordinary expensive chips being more capable doesn't change the economical situation.

I am tickled that OOM can mean "out of memory" in another context. You clearly meant "orders of magnitude".

Two wrongs do not make a right?

Arguably they already did with the "cloud native" systems. There were plenty of examples personally known to me in the mid and late 2010s of smaller tech companies trying to run production PostgreSQL on 8-16 GB of RAM because they didn't want to pay the cloud RAM tax. Many "cloud native" systems were designed under these (mostly artificial IMO) RAM constraints.

It's not 1:1 when you consider inflation either. Ram is still cheaper when inflation is a factor.

China often exhibits tremendous internal market competition, so it's possible that different Chinese suppliers will race each other to the bottom (Chinese firms are really good at suriving on ultra-thin margins) making prices even lower than 10% below the premium providers.

More competition will drive down the market price, so it'll be 10% below a price that is lower than what we have currently. Obviously it's not gonna go down immediately, but more supply will definitely bring down prices. Obviously, this is very bad for the existing memory makers, since these boom prices will not last forever, and the Chinese aren't gonna stop selling memory once they are in the market.

Will they..? It seems equally (or perhaps more) likely that we'll increasingly see vibe coded browser or Electron based applications as the bar is now lower to build such a thing.

Can you back that up with anything about semi-recent nodes? The voltages are so fragile that I'm not convinced you would actually save space once you adjust the design to handle more levels.

do you have a reference to exact / realistic scaling laws for the leakage currents as function of capacitor/dielectric dimensions and access transistor dimensions? using 4 (or 2^N) voltage levels stores 2 (or N) bits, so we can afford to make the structures larger why would this approach make sense for NAND flash but not DRAM?