[steveBK123]

> The $20-200 LLM plans are all subsidized and aren't paying for themselves. Something has to give here.

Whats interesting to me as well as much as companies are pushing AI adoption, i have started to hear AI token spend limits enforced across a few companies, so its not entirely clear that b2b can make them profitable yet either.

If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.

It’s not like “best” has won any other b2b arms race in the past.

[operatingthetan]

>If all the models reach good enough, then low cost provider would win. Gemini seems like a safer bet since Google controls more of the stack / has more efficiencies / cross selling / etc.

Gemini is the best deal too. For $20: you get multiple quotas per day across the products (web, CLI, antigravity, AI Studio) 2tb of cloud storage, and you can family share the plan.

[SpicyLemonZest]

I don't know Gemini's pricing model in detail, but in general pricing doesn't generalize well between personal/hobbyist and enterprise use. Consumer pricing of variable costs is a balancing act, and most Gemini users aren't going to be anywhere near the quota; a company of 1000 can't always buy for $20,000 what 1000 random users with $20 personal plans are theoretically capped at.

[steveBK123]

Ultimately though in the long run.. They invented the tech, have a large cashflow generating business subsidizing R&D as well as sales, with network effect of existing B2B relationships.

Further they have their own TPUs, datacenters, etc on which to run their models.

Plus existing data they've squirreled away over the preceding 30 years from books, web, etc.

Just seems like a lot of efficiencies if its going to come down to cost.

[cmiles8]

In large part because most companies have a set budget for IT spend. Thats how “normal” profitable companies operate outside this cash burning bonanza that’s going on.

And in that reality one can’t just magically spend a bunch more on some fancy new thing, especially when said fancy new thing isn’t retuning value. So “token limits” and cost controls on B2B is entirely expected here.

[steveBK123]

> especially when said fancy new thing isn’t retuning value

I think this is the key element. Either they can't measure the value, or it's far far lower than anyone wants to believe, or both.

I think the problem is less that it makes some coding tasks XX% faster, but that the end to end of a SWEs roles tasks is only improved by some much smaller Y%.

If a CTO sets $10k/year spend limits on $500k SWEs.. they must not believe any of the hype.

[bobthepanda]

The problem is that AGI fantasy aside, CTOs at companies are expected to deliver results today and tomorrow. Better to let somebody else hold the bag and train models, then once it finally works as advertised you can ease on the brakes.