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Comment by dcss_gardener | Hacker News Reader

The current crop of flash models are more comparable to sonnet than opus but they are very affordable.

The reality is that the subscriptions are heavily subsidized. Pretty much every sub that's not run by one of the money-burning frontier labs has had to drop it or dramatically increase prices and lower limits in the last few months. Cheap tokens are an acquisition tool, not a real product. It sounds dramatic but it really is the drug dealer sales funnel.

At some point they're going to drop the real prices in your lab and you're going to have to figure out how to pay that much or pay someone else a lot less. Better to get a handle on it now.

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> At some point they're going to drop the real prices in your lab

The real price for tokens at a specific level of intelligence is dropping rapidly. Between models improving and new hardware getting faster, I think prices will be going down, not up.

> Better to get a handle on it now.

I experiment with a lot of providers and models. I strongly disagree that anyone needs to start migrating now in preparation for prices maybe going up in the future.

It doesn’t make sense. Deal with a price increase when it happens, if it does.

Switching models and providers isn’t some huge lift. I can jump to a new model or even hardness and get a feel for it in a day or two. It’s not some huge undertaking that requires preparation and planning.

If prices go up, try something at that point in time. Don’t worry about it until then.

When Claude Code subscriptions really started to catch on, there was a popular idea on HN that Anthropic's end game was that basically every dev adjacent role would need to pay for a $200/mo coding plan.

Then, both Anthropic and OpenAI in lockstep developed a enterprise pricing structure that openly coerced large businesses to pay API prices where it was feasible to spend $200/day rather than the comparatively cheap $200/mo.

Even if token pricing relative to intelligence does trend down over time, that doesn't mean the pricing structure will actually translate to lower costs, particularly in the cash cow B2B market.

Its insane, I don't possibly understand how they convinced companies to pay 30x

What was the alternative? It takes time for the open weight ecosystem to develop.

Companies still believe they have IP to protect. Even when all they do are basic CRUD systems or on the verge of collapsing if they don’t renew some contracts.

From experience, if you work somewhere with very disconnected higher ups a sales person shows what your token usage is vs spend on the monthly subs for whatever set of users you have and then show an API price with a sample bill for even “more users” at that same number of tokens that is 30% lower. The crux of course being that your existing user base is not going to use fewer toke a just because you signed more people up and have a discount for the status quo.

Then when you consolidate all users to a single provider you find out you have a 2x to 3x larger bill because you… logically have more users at the same average token spend than the quote.

At my previous job, all while managing a full team, I did a lot of porting of legacy apps to modern standards to maintain various obligations. It was AI gen work in between meetings and paperwork. It was seen as such a success that I was asked to move to an IC role to focus on it within the “Elite new products team” that was supposed to be all AI and the latest tech. I showed up to find that they were pushing out low quality manually written code in 12 hour days six days per week to appear like LLMs were in use to save face because they lacked a token budget or the skills to properly manage one under the APIs. They had dismissed someone who had spent multiple thousands per month on Agent swarms. It was the perfect situation to make their 3x budget issue a 10-30x budget spend issue.

For many many reasons I left that job and got a new one but that was the cherry on top.

I see you are not familiar with enterprise IT hardware and software purchasing...

The API/subscription split as always there. I don’t know why you’re talking about it as a bait-and-switch development.

That doesn’t change anything about what I said, though. The relative price per task or price per unit intelligence is also going down in the APIs too.

> Even if token pricing relative to intelligence does trend down over time, that doesn't mean the pricing structure will actually translate to lower costs, particularly in the cash cow B2B market.

What are you talking about? The APIs serve the same models as the subscriptions. Unless you think the price of APIs has been going up (it has not) this argument doesn’t make sense

It's not obvious the subsidization will end. Loss leaders are a thing. Most enterprise at this point are paying API pricing

To better predict what they'll do with it we'd need to know the proportion of token usage via API vs subscription. Keeping an affordable, slightly unprofitable subscription to get people in isn't a bad idea. They also get marketing benefits from the word of mouth

Also, some subset of developers on subscriptions are going to develop products that use the API, and some of those products are going to be successful.

In the optimistic case you describe, what smart customers want to watch out for is being lured into vibing your projects into such byzantine slop-complexity that subscription plans and trailing models are no longer sufficient to make progress on them.

Vibe-coders talk about surrendering understanding to the models, trusting that there will always be a model able to overcome and work through any technical debt they happen to accumulate, but the danger that still lurks there (at least for the naive) is that you'll need increasingly large contexts, increasingly sophisticated models, and increasingly large token spends just to keep that ball rolling.

Between profitable enterprise accounts being ineligible for subscription, eager but busy people paying for underutilized subscriptions, and naive vibe-coders falling into their pit trap, you can indeed imagine subsidized subscription accounts being available for a long time and remaining an effective value hack for people careful enough not to fall into the pit trap. But only insofar as they are that careful.

Also they can always find another way to make money. Make subscription users product and sell some analytics like "show most trending project being built this week".

You cannot predict the future, but you can identify risks and attribute a likelihood. A risk is that the subsidized inference will either end or be reduced significantly in the next 1-2y. If you think the likelihood is high enough it makes sense to ensure your systems are prepared for it.

That’s risk management 101

> It's not obvious the subsidization will end. Loss leaders are a thing.

Loss leaders are a thing so long as they actually do lead somewhere. If your primary value proposition is conveyed by the loss leader itself, where do you go from there?

>At some point they're going to drop the real prices in your lab and you're going to have to figure out how to pay that much or pay someone else a lot less. Better to get a handle on it now.

So just wait until that happens? What's the point of scrimping and saving now? Not to mention you're paying for a premium in the meantime.

I don’t disagree really and it is mostly what I am doing. I put probably like 20% of my work through open weights.

It does make me sharper I think. If you only ever use claude or whatever you don’t even really know exactly how tied to it you are.

Funny enough the drug dealer thing still holds. A deal’s a deal if you’re going to buy it anyway.

(meta commentary) really gnarly word choice: "drop" in "they're going to drop the real prices in your lab"?

I took your meaning as "they're gonna drop [a bad surprise on you by raising] the real prices"... so at least it's not quite as tortured as the ambiguous "support for version N dropped today" (where you often can't even infer the direction from context).

this isn't just a tangent, I'm having trouble understanding the point you're trying to make, which hinges entirely on deciding if you meant "drop" literally

They meant "they're going to drop a bad surprise by charging you API prices", so yes, a better wording would be "they're going to give you a bad surprise in the form of forced API pricing".

The term "drop" becoming a synonym for "release", "put out" or "put into effect" for things outside of music/albums is one of the most confusing linguistic innovations of the last decade.

“Lab” is a typo, it should be “lap”.

“Drop [an unwelcome surprise] in your lap” is a common English idiom.

> At some point they're going to drop the real prices in your lab and you're going to have to figure out how to pay that much or pay someone else a lot less.

This only applies under the assumption that everyone tokenmaxxes their subscription.

I have visibility across a few different Claude team subscriptions. I'd say roughly 10% of people max their subscriptions.

I think I've only seen one organization where the under-used subs don't more than pay for the tokenmaxxed ones.

And that is ignoring the 90% margin that API inference runs at.

At some point companies will need to have the “scary” conversation about the value proposition of adding another human to the team, or adding a comparable amount of token spend to the team.

$1k/person sounds like a lot, but a ten person team at $1k token burn / head / month is spending $120k. How much does a new hire cost, tco? Does velocity from one more person compare with velocity from one more person’s worth of tokens?

Sure, learning to be efficient matters. So does taking the time to consider cost vs alternative. You might be surprised by what you find, in either direction.

Counter point - models get better, ways to run them gets optimized and hardware will eventually come down in price.

The share of tasks where "cheaper" models are enough also increases for same reason. For majority of use cases it will quickly become race to the bottom. And that means part of the pie for the "premium" models of frontier AI labs will quickly become smaller and smaller.

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