Openai's Cash Burn Will Be One of the Big Bubble Questions of 2026

That being said, if I was Sam Altman I'd also be stocking up on yachts, mansions and gold plated toilets while the books are still private. If there's $10bn a year in outgoings no one's going to notice a million here and there.

That's what the words mean in this context.

OpenAI ask for 1m GPUs for a month, Anthropic ask for 2m, the government data center only has 500,000, and a new startup wants 750,000 as well.

Do you hand them out to the most convincing pitch? Hopefully not to the biggest donor to your campaign.

Now the most successful AI lab is the one that's best at pitching the government for additional resources.

Why would you want my money to be used to build datacenter that won’t benefit me ? I might use a LLM once a month, many people never use it.

Let the one who use it pay for it.

I see no argument why the government would jump into a hype cycle and start building infra that speculative startups are interested in. Why would they take on that risk compared to private investors, and how would they decide to back that over mammoth cloning infra or whatever other startups are doing?

Everything is happening exactly as it should. If the "bubble" "pops", that's just the economic laws doing what they naturally do.

Hmm, what about member-owned coöperatives? Like what we have for stock exchanges.

I know sama says they aren’t trying to train new models, but he’s also a known liar and would definitely try to spin systemic failure.

Their investors surely do (absent outrageous fraud).

> For all we know, they could be accumulating capital to weather an AI winter.

If they were, their investors would be freaking out (or complicit in the resulting fraud). This seems unlikely. In point of fact it seems like they're playing commodities market-cornering games[1] with their excess cash, which implies strongly that they know how to spend it even if they don't have anything useful to spend it on.

[1] Again c.f. fraud

No one knows whether the base model has changed, but 4o was not a base model, and neither is 5.x. Although I would be kind of surprised if the base model hadn't also changed, FWIW: they've significantly advanced their synthetic data generation pipeline (as made obvious via their gpt-oss-120b release, which allegedly was entirely generated from their synthetic data pipelines), which is a little silly if they're not using it to augment pretraining/midtraining for the models they actually make money from. But either way, 5.x isn't just a prompt chain and routing on top of 4o.

At the very least they made GPT 4.5, which was pretty clearly trained from scratch. It was possibly what they wanted GPT-5 to be but they made a wrong scaling prediction, people simply weren't ready to pay that much money.

This isn't really accurate.

Firstly, GPT4.5 was a new training run, and it is unclear how many other failed training runs they did.

Secondly "all subsequent models are routing systems and prompt chains built on top of 4" is completely wrong. The models after gpt4o were all post-trained differently using reinforcement learning. That is a substantial expense.

Finally, it seems like GPT5.2 is a new training run - or at least the training cut off date is different. Even if they didn't do a full run it must have been a very large run.

https://www.theinformation.com/articles/openai-says-business...

https://epoch.ai/blog/training-compute-of-frontier-ai-models...

Doubtful. This would be the very antithesis of the Silicon Valley way.

1. Google books, which they legally scanned. No dubious training sets for them. They also regularly scrape the entire internet. And they have YouTube. Easy access to the best training data, all legally.

2. Direct access to the biggest search index. When you ask ChatGPT to search for something it is basically just doing what we do but a bit faster. Google can be much smarter, and because it has direct access it's also faster. Search is a huge use case of these services.

3. They have existing services like Android, Gmail, Google Maps, Photos, Assistant/Home etc. that they can integrate into their AI.

The difference in model capability seems to be marginal at best, or even in Google's favour.

OpenAI has "it's not Google" going for it, and also AI brand recognition (everyone knows what ChatGPT is). Tbh I doubt that will be enough.

>whereas OpenAI has a clear opportunity with advertising.

Personally, having "a clear opportunity with advertising" feels like a last ditch effort for a company that promised the moon in solving all the hard problems in the world.

Some players have to play, like google, some players want to play like USA vs. China.

Besides that, chatting with an LLM is very very convincing. Normal non technical people can see what 'this thing' can already do and as long as the progress is continuing as fast as it currently is, its still a very easy to sell future.