Make new mathematical discoveries, and the security capabilities of the closed models have not yet been rivaled by open ones.

Also, just because a model is open now doesn't mean it will always be. If/when China or meta catches up to the frontier, they'll instantly go closed source. China, the biggest surveillance state in the world, would love to have all user data pouring in to its servers. It's just a business strategy, they're not doing it out of the kindness of their hearts.

The moat is money. How do you get more money? Point to your moat and ask for more money!

> If you're paying $250k/year for a software engineer, it likely makes sense to have them spend $10k/year

Would be nice. I feel like the more you go towards the 3rd world (or tbh anywhere not in the US), the more this calculus shifts, probably all the way to underspecced workstations, no IDE licenses (e.g. JetBrains) and also no investment into tokens or whatever.

Also, 10k USD per year seems a bit low, I'm not tokenmaxxing but my non-subscription usage equivalent would be around 3000-6000 USD per month, though obviously with models like Kimi K3 and GLM 5.3 it would be way more sensible compared to Anthropic.

> The Chinese companies will need to pay their bills eventually too.

What bills? Deepseek has been profitable for long time.

Their purchasing costs are much lower proportionally.

China has cheaper electricity and a more capable grid for the industrial type usage levels they need to drive.

While not today, very soon every company, of every complexity will run local models. It's not in a companies interest to hand over its domain expertise, data, and proprietary IP for a increase in productivity. Most will quickly realize it makes sense to run their own weights. This will be commonplace once tooling and training infrastructure is commoditized.

Enterprises don't even want to self-host webservers, and those are about a thousand times easier to do than self-hosting an AI model

Your comparison is wrong

It's not an expensive car vs. any car.

It's car vs. no car.

It's less fungible than you think.

Below a certain threshold prices are effectively all the same.

Companies pay API prices because part of the bundle is a trust anchor / liability shield: "we bought Anthropic's thing! We didn't risk it! We paid for ZDR!"

Let's try a thought experiment. It's not subsidized. It's not "worth" the tens of times it costs if accessed through API. Let's drop the subsidy word, they're selling you a product, and they're trying to sell other people a similar product at 30x the price with some excuses. If either (or both) turns out to be unsustainable, they haven't been subsidizing you, they just had a crap business model (or a perfectly good one, if the goal was an inflated valuation, an IPO and then a crash once the losses are socialized).

They might raise the price, but I don't think they will ever get rid of the $20 tier. It is way too consumer friendly and likely has the highest percentage of users that aren't abusing their quota limits. A layperson will be extremely hard pressed to create an API key, know what to do with it, put money in their account. People want an easy subscription.

Anthropic’s revenue run rate just hit $50B, in a market that didn’t exist 5 years ago and was 10% of its current size 1 year ago. They are, by far, the fastest growing company in human history. The demand for “rockets” has been pretty high and growing ever since they started supplying it.

Anthropic and its investors/customers don’t need random internet commenter’s permission to decide whether or not something is worth doing or justified.

Personally I think when something doesn’t make sense to you, you should try to figure out why it makes sense to other people, and whether they might have different needs/constraints/incentives/skills/knowledge.

Why might people spend more on AI as it gets better, rather than less? Could they, perhaps, allow for entirely new kinds of capabilities and products that hacker news commenters have not yet seen? As they have done every year for 3 straight years (hacker news has been wrong in exactly the same way every time, btw)? Might some people prefer to spend $10/day to work with the most capable AI available, due to the amount they use it while doing their job, and its effect on output? Do some people use AI for more than just tinkering with open source harnesses? Could it be that when you don’t understand something, there really is a way to explain it, that isn’t “everybody else must be stupid”?