Hacker News Reader

Hacker News

Comment by fooker | Hacker News Reader

Parent Full thread

fooker

> It might become cheaper or it might not

If it does not, this is going to be first technology in the history of mankind that has not become cheaper.

(But anyway, it already costs half compared to last year)

View on HN

> But anyway, it already costs half compared to last year

You could not have bought Claude Opus 4.5 at any price one year ago I'm quite certain. The things that were available cost half of what they did then, and there are new things available. These are both true.

I'm agreeing with you, to be clear.

There are two pieces I expect to continue: inference for existing models will continue to get cheaper. Models will continue to get better.

Three things, actually.

The "hitting a wall" / "plateau" people will continue to be loud and wrong. Just as they have been since 2018[0].

[0]: https://blog.irvingwb.com/blog/2018/09/a-critical-appraisal-...

interesting post. i wonder if these people go back and introspect on how incorrect they have been? do they feel the need to address it?

No, people do not do that.

This is harmless when it comes to tech opinions but causes real damage in politics and activism.

People get really attached to ideals and ideas, and keep sticking to those after they fail to work again and again.

i don't think it is harmless or we are incentivising people to just say whatever they want without any care for truth. people's reputations should be attached to their predictions.

Some people definitely do but how do they go and address it? A fresh example in that it addresses pure misinformation. I just screwed up and told some neighbors garbage collection was delayed for a day because of almost 2ft of snow. Turns out it was just food waste and I was distracted checking the app and read the notification poorly.

I went back to tell them (do not know them at all just everyone is chattier digging out of a storm) and they were not there. Feel terrible and no real viable remedy. Hope they check themselves and realize I am an idiot. Even harder on the internet.

Do _you_ do that?

i try to yes

> The "hitting a wall" / "plateau" people will continue to be loud and wrong. Just as they have been since 2018[0].

Everybody who bet against Moore's Law was wrong ... until they weren't.

And AI is the reaction to Moore's Law having broken. Nobody gave one iota of damn about trying to make programming easier until the chips couldn't double in speed anymore.

This is exactly backwards: Dennard scaling stopped. Moore’s Law has continued and it’s what made training and running inference on these models practical at interactive timescales.

You are technically correct. The best kind of correct.

However, most people don't know the difference between the proper Moore's Law scaling (the cost of a transistor halves every 2 years) which is still continuing (sort of) and the colloquial version (the speed of a transistor doubles every 2 years) which got broken when Dennard scaling ran out. To them, Moore's Law just broke.

Nevertheless, you are reinforcing my point. Nobody gave a damn about improving the "programming" side of things until the hardware side stopped speeding up.

And rather than try to apply some human brainpower to fix the "programming" side, they threw a hideous number of those free (except for the electricity--but we don't mention that--LOL) transistors at the wall to create a broken, buggy, unpredictable machine simulacrum of a "programmer".

(Side note: And to be fair, it looks like even the strong form of Moore's Law is finally slowing down, too)

If you can turn a few dollars of electricity per hour into a junior-level programmer who never gets bored, tired, or needs breaks, that fundamentally changes the economics of information technology.

And in fact, the agentic looped LLMs are executing much better than that today. They could stop advancing right now and still be revolutionary.

As a user of LLMs since GPT-3 there was noticeable stagnation in LLM utility after the release of GPT-4. But it seems the RLHF, tool calling, and UI have all come together in the last 12 months. I used to wonder what fools could be finding them so useful to claim a 10x multiplier - even as a user myself. These days I’m feeling more and more efficiency gains with Claude Code.

That's the thing people are missing, the models plateaued a while ago, still making minor gains to this day, but not huge ones. The difference is now we've had time to figure out the tooling. I think there's still a ton of ground to cover there and maybe the models will improve given that the extra time, but I think it's foolish to consider people who predicted that completely wrong. There are also a lot of mathematical concerns that will cause problems in the near and distant future. Infinite progress is far from a given, we're already way behind where all the boosters thought we'd be my now.

I believe Sam Altman, perhaps the greatest grifter in today’s Silicon Valley, claimed that software engineering would be obsolete by the end of last year.

That's not true. Many technologies get more expensive over time, as labor gets more expensive or as certain skills fall by the wayside, not everything is mass market. Have you tried getting a grandfather clock repaired lately?

"repairing a unique clock" getting costlier doesn't mean technology hasn't gotten cheaper.

check out whether clocks have gotten cheaper in general. the answer is that it has.

there is no economy of scale here in repairing a single clock. its not relevant to bring it up here.

Clocks prices have gone up since 2020. Unless a cheaper better way to make clocks has emerged inflation causes prices to grow.

Luxury watches have gone up, 'clocks' as a technology is cheaper than ever.

You can buy one for 90 cents on temu.

The landing cost for that 90 cent watch has gone way up. Shipping and to some degree taxes has pushed the price higher.

that's not the technology

of course it's silly to talk about manufacturing methods and yield and cost efficiency without having an economy to embed all of this into, but ... technology got cheaper means that we have practical knowledge of how to make cheap clocks (given certain supply chains, given certain volume, and so and so)

we can make very cheap very accurate clocks that can be embedded into whatever devices, but it requires the availability of fabs capable of doing MEMS components, supply materials, etc.

not true, clocks have gone down after accounting for inflation. verified using ChatGPT.

You can't account for inflation because the price increase is inflation.

this is not true

you can look at a basket of goods that doesn't have your specific product and compare directly

but inflation is the general price level increase, this can be used as a deflator to get the price of whatever product in past/future money amount to see how the price of the product changed in "real" terms (ie. relative to the general price level change)

You cannot verify anything using a tool that cannot validate truth.

Instead of advancing tenuous examples you could suggest a realistic mechanism by which costs could rise, such as a Chinese advance on Taiwan, effecting TSMC, etc.

No. You don't get to make "technology gets more expensive over time" statements for deprecated technologies.

Getting a bespoke flintstone axe is also pretty expensive, and has also absolutely no relevance to modern life.

These discussions must, if they are to be useful, center in a population experience, not in unique personal moments.

okay how about the Francis Scott Key Bridge?

https://marylandmatters.org/2025/11/17/key-bridge-replacemen...

You will get a different bridge. With very different technology. Same as "I can't repair my grandfather clock cheaply".

In general, there are several things that are true for bridges that aren't true for most technology:

* Technology has massively improved, but most people are not realizing that. (E.g. the Bay Bridge cost significantly more than the previous version, but that's because we'd like to not fall down again in the next earthquake) * We still have little idea how to reason about the cost of bridges in general. (Seriously. It's an active research topic) * It's a tiny market, with the major vendors forming an oligopoly * It's infrastructure, not a standard good * The buy side is almost exclusively governments.

All of these mean expensive goods that are completely non-repeatable. You can't build the same bridge again. And on top of that, in a distorted market.

But sure, the cost of "one bridge, please" has gone up over time.

> But sure, the cost of "one bridge, please" has gone up over time.

Even if you adjust for inflation?

Depends, do we care about TCO? Also, can I pick the set of bridges I compare?

OK, kidding aside: If you deeply care, you can probably mine the Federal Highway Administration's bridge construction database: https://fhwaapps.fhwa.dot.gov/upacsp/tm?transName=MenuSystem...

I don't think the question is answerable in a meaningful way. Bridges are one-off projects with long life spans, comparing cost over time requires a lot of squinting just so.

This seems largely the same as any other technology. The prices of new technologies go down initially as we scale up and optimize it's production, but as soon as demand fades, due to newer technology or whatever, the cost of that technology goes up again.

Bought any RAM lately? Phone? GPU in the last decade?

The latest iphone has gone down in price? It's double. I guess the marketing is working.

"Pens are not cheaper, look at this Montblanc" is not a good faith response.

'84 Motorola DynaTAC - ~$12k AfI (adjusted for inflation)

'89 MicroTAC ~$8k AfI

'96 StarTAC ~$2k AfI

`07 iPhone ~$673 AfI

The current average smartphone sells for around $280. Phones are getting cheaper.

Phones, or smartphones?

I purchased a 5T drive in 2019 and the price is higher now despite newer better drives going on the market since.

Not much has down in price over the last few years.

Price volatility exists.

Meanwhile the overall price of storage has been going down consistently: https://ourworldindata.org/grapher/historical-cost-of-comput...

Repairing grandfather clocks isn't more expensive now because it's gotten any harder; it's because the popularity of grandfather clocks is basically nonexistent compared to anything else to tell time.

Doesn't need to be any particular reason to disprove the notion that technology only gets cheaper.

Time-keeping is vastly cheaper. People don't want grandfather clocks. They want to tell time. And they can, more accurately, more easily, and much cheaper than their ancestors.

Or riding in an uber?

Sure, running an LLM is cheaper, but the way we use LLMs now requires way more tokens than last year.

ok but the capabilities are also rising. what point are you trying to make?

That it's not getting cheaper?

But it is, capability adjusted, which is the only way it makes sense. You can definitely produce last years capability at a huge discount.

you are wrong. https://epoch.ai/data-insights/llm-inference-price-trends

this is accounting for the fact that more tokens are used.

The chart shows that they’re right though. Newer models cost more than older models. Sure they’re better but that’s moot if older models are not available or can’t solve the problem they’re tasked with.

this is incorrect. the cost to achieve the same task by old models is way higher than by new models.

> Newer models cost more than older models

where did you see this?

On the link you shared, 4o vs 3.5 turbo price per 1m tokens.

There’s no such thing as ”same task by old model”, you might get comparable results or you might not (and this is why the comparison fail, it’s not a comparison), the reason you pick the newer models is to increase chances of getting a good result.

> The dataset for this insight combines data on large language model (LLM) API prices and benchmark scores from Artificial Analysis and Epoch AI. We used this dataset to identify the lowest-priced LLMs that match or exceed a given score on a benchmark. We then fit a log-linear regression model to the prices of these LLMs over time, to measure the rate of decrease in price. We applied the same method to several benchmarks (e.g. MMLU, HumanEval) and performance thresholds (e.g. GPT-3.5 level, GPT-4o level) to determine the variation across performance metrics

This should answer. In your case, GPT-3.5 definitely is cheaper per token than 4o but much much less capable. So they used a model that is cheaper than GPT-3.5 that achieved better performance for the analysis.

OpenAI has always priced newer models lower than older ones.

https://platform.openai.com/docs/pricing

Not according to their pricing table. Then again I’m not sure what OpenAI model versions even mean anymore, but I would assume 5.2 is in the same family as 5 and 5.2-pro as 5-pro

Check GPT 5.2 vs it's predecessor the 'o' series of reasoning models.

not true! 4o was costlier than 3.5 turbo

10x more tokens today cost less than than half of X tokens from ~mid 2024.

Not true. Bitcoin has continued to rise in cost since its introduction (as in the aggregate cost incurred to run the network).

LLMs will face their own challenges with respect to reducing costs, since self-attention grows quadratically. These are still early days, so there remains a lot of low hanging fruit in terms of optimizations, but all of that becomes negligible in the face of quadratic attention.

For Bitcoin that’s by design!

> bitcoin

so close! that is a commodity

I don't think computation is going to become more expensive, but there are techs that have become so: Nuclear power plants. Mobile phones. Oil extraction.

(Oil rampdown is a survival imperative due to the climate catastrophe so there it's a very positive thing of course, though not sufficient...)

There are plenty of technologies that have not become cheaper, or at least not cheap enough, to go big and change the world. You probably haven't heard of them because obviously they didn't succeed.

cheaper doesnt mean cheap enough to be viable after the bills come due

Supersonic jet engines, rockets to the moon, nuclear power plants, etc. etc. all have become more expensive. Superconductors were discovered in 1911, and we have been making them for as long as we have been making transistors in the 1950s, yet superconductors show no sign of becoming cheaper any time soon.

There have been plenty of technologies in history which do not in fact become cheaper. LLMs are very likely to become such, as I suspect their usefulness will be superseded by cheaper (much cheaper in fact) specialized models.

Concorde?

Reply on news.ycombinator.com