Yes, large corporations frequently pay orders of magnitude more for slightly better software. That's why Oracle produces the best stuff on the planet.

The real issue is that Deepseek has a 99.7% chance. So I can run it 10 times until it works and still pay 1/10 the money.

Actually opposite occurs. Big businesses are ok with a mediocre but cheaper result. Very few are willing to pay such cost. Just look at tech wages and the distributions

That 70% chance of success goes to 99.9% in 6 repetitions.

Big businesses might pay $1000 vs $60 for certain tasks, but that won't work out well at scale.

Except businesses are going the opposite direction here. The lack of stickiness makes the “premium” argument hard to play. Oracle won because swapping databases is a giant PITA. Swapping models requires almost no effort for most uses. And because of that enterprises are all building model marketplaces where providers have to compete on price performance.

Most folks I know can choose from any of the big labs or open weight models and they get billed internally for tokens against their budget. There’s little incentive to no switch to the lower cost closers.

This setup is a nightmare scenario for the big labs trying to execute the traditional enterprise sales plays. Those only work if your product is sticky and AI models are one of the least sticky things in the history of tech.

Big business doesn't pay more for better, but the do pay more for predictability, support and targeted outcomes. They will happily trade a chance at 100% better results for 10% less chance of unplanned outcomes

The business I work for is absolutely sensitive to 10 vs 1000, depending on the task. And it's a multi-billion dollar business. 1000/task may not be much on it's own, but there are a lot of tasks.

Also, is it really 99.9% vs 70%, or 99.9% vs 99%?

It was more of a “sorry, not sorry”