Comment by surajrmal
5 hours ago
What enterprises pay for is all that matters. They pay insane amounts for a lot of things I would never do personally, but I'm not the target demographic in those cases.
5 hours ago
What enterprises pay for is all that matters. They pay insane amounts for a lot of things I would never do personally, but I'm not the target demographic in those cases.
Right, and it's often very sane. If you're paying $250k/year for a software engineer, it likely makes sense to have them spend $10k/year on tokens from the best available model rather than trying to save a few thousand with random Chinese models that may or may not be good enough.
The Chinese companies will need to pay their bills eventually too.
> The Chinese companies will need to pay their bills eventually too.
What bills? Deepseek has been profitable for long time.
Do you have a source I can read? All I see on Google are random blog posts mostly debunking that idea. Profit margins on API tokens isn't the same as running a profitable long term business, or bringing returns on the large amount of funding they got.
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.
Data centers don't really cost less in China. Perhaps even more due to trade restrictions and the difficulty of smuggling the chips in.
Electricity is a small part of the bill.
Wouldn't enterprises rather run their own models locally?
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