I see exactly opposite . Chinese models fails under any complex scenarios, while us labs raise the price , that's a sign of confidence.

Both can be true. They can be charging what the market will bear, and still be charging less than their costs of running it.

> I don't think anyone has a firm grasp on actual inference costs -- including the research and training that has gone into those models

We know roughly how much these companies spend and what their revenues are. Based on that, they'd have to more than double revenue (without spending more money) just to stay even, and that's not good enough given how deep in the hole they are.

> OpenAI and Anthropic are heavily subsidizing their inference -- no wait, they are charging the most they can get away with before going public. Where is the truth?

Both are true. I mean, I'd be willing to spend a bit more than I do now, but not more than double, and neither are most companies. The company I work for is currently investigating how to reduce LLM spend, not looking to spend more.

> OpenAI and Anthropic are heavily subsidizing their inference -- no wait, they are charging the most they can get away with before going public. Where is the truth?

Both. They are charging the most they can get away with and that amount is still heavily subsidized by VC capital.

We pay by token at work. I just finished one session with Opus that was 4000 dollars. In about three days.

Now that 200USD subscription starts to feel cheap...

> I don't think anyone has a firm grasp on actual inference costs.

There are huge numbers of users (myself included) that do have an exact idea of what inference costs on open models. Because we can buy tokens from 3rd parties that have no motivation to subsidize our use. That's to say, there's a fair marketplace[1] and we're hanging out there.

If you want to say "I don't think anyone has a firm grasp on actual inference costs on these proprietary/closed models", then I could agree with that.

[1]: https://openrouter.ai/rankings#leaderboard

We have a firm grasp on actual inference costs from the various open weights model providers on OpenRouter. They don't have the money to subsidize inference and it's quite a competitive market, so the prices are representative of the costs.

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Anthropic and OpenAI won't be around in 1-2 decades if this is their long term plan. People are not going to revert, but go elsewhere. China is proving that it can be done cheaper.

Just a personal anecdote but I have not hit any more thresholds or limits since switching to the MAX plan and so far, it's been worth it. But I do wonder how long even this will last...

I have the $100 plan and had almost never run out of credits until I started using the ultracode / workstreams feature w/Opus 4.8..at which point I managed to blow the full 6 hour allocation in like 20 minutes, or so. In fairness, it did some amazing things with the extracted information, but it also strongly suggested that I'd need the $200 subscription *plus* a budget for extra usage.

> Nothing is subsidized. Subscriptions are profitable for both Anthropic and OpenAI.

Even if subscriptions are locally profitable (i. e., the cost of the subscription covers the cost of inference), they're still subsidized because they don't cover training and running the company; otherwise, these companies would be profitable.

"Nothing is subsidized" is a wild take. They might be making money on some users, perhaps even most users, but certainly not all. Also, "subsidized" doesn't just mean on compute.

That's interesting. Do you have anything to back that claim up?

"Nothing is subsidized"

So they are profitable?

I think you are mismatching accounting terms.

You can't say the 'subscriptions' are profitable without accounting for the cost of making the model that is the source of the subscription.

They are heavily subsidized by the shareholders. Investing, running at a loss, with hope of some future profitability.