Everyone who was paying attention even a little bit has known this would be the trajectory from the beginning. And we haven’t even gotten to the crazy price hikes per token that are coming.
And we haven’t even gotten to the crazy price hikes per token that are coming.
Why do you think that?
IMHO, API prices are likely to drop over time as we scale up and efficiencies are found, combined with general pricing pressure from the competition… SOTA models will continue to have SOTA prices, of course, but reasonable priced distilled and open weights models are already common.
A consequence of API prices dropping is that “heavily discounted” consumer plans will also adjust and won’t be so generous relative to API prices.
IMHO, API prices are likely to drop over time as we scale up and efficiencies are found, combined with general pricing pressure from the competition… SOTA models will continue to have SOTA prices, of course, but reasonable priced distilled and open weights models are already common.
Some of this seems like wishful thinking to me.
“as we scale up” We already have large data centers, and, if anything, “scaling up” is just driving up expenses for debt and hardware. The real problem with AI, relative to the internet boom, is that the more you use it, the more expensive it is. The economies of scale to be taken advantage of are minimal.
I do think price of compute will come down, but exactly because people will be running their own open source models on their own hardware instead of Sam Altman to stack GPUs in a warehouse, but it will still be too expensive and inaccurate.
And we’re still headed for a financial cliff in this scenario.
Like a fraction of a percent of people will run their own models. It won’t influence price. Remember that coders/tech people are only a minority of users.
Oh, I see. I was mistaken. I thought tech companies were OpenAI’s major customers, and they certainly could make their own data centers for internal work, and that coders–that minority of users–were the only ones likely to pay full price for tokens, the rest of us wouldn´t be willing to pay full fare for a machine that is right most of the time sort of. Thanks for setting me straight on that.
Some large companies do it … but I think you greatly overestimate the willingness of large enterprises to build and maintain their own infra. Once a company has lost the competency (and many have), it’s hard to get it back. There are always pockets of people with the right skillset in a large org, but they mostly don’t want to do DC work anymore. Team/personal servers and beefy laptops, otoh…
Of course they want to turn the corner and ideally keep all their infra, but they might need to restructure their debts if/when the creditors come knocking.
BUT: they have a money printing machine with inference… Enterprise is where most of the money is made, as they pay (closer to) API prices… consumer & small business plans are heavily discounted in comparison, with mostly underutilized use-it-or-lose it plans. They’d be stupid if they were making an opex loss on inference.
As for why API prices are dropping? Competition is a bitch… but they seem willing and able to play the game for now.
They were supposed to do their IPO and have positive cash flow already. Time is running out before investors are getting antsy and there’s no more money available for scaling up.
They gobbled up the easy money… now they have to work harder for more, and yeah, they may have to slow down a bit and embrace fiscal responsibility… I expect to see restructuring of debts along the way, but I’d be very surprised to see any of the major US based players implode.
Both Anthropic & OpenAI have debt repayments coming up in 2027 that:
cannot be restructured
cannot be postponed
they absolutely cannot pay back without even more VC money, and that faucet is being cut off right now.
Well then. I stand corrected. The random Internet person with unprecedented access into the books & private financial dealings of two major competitors has an air-tight argument.
I suggest we come back to this thread in a year’s time and see how it is playing out.
Look up some well known critics in the AI space and you will see a bunch of information that aligns with OPs statements. Its always been scheduled for Q2/Q3 2027.
Everyone who was paying attention even a little bit has known this would be the trajectory from the beginning. And we haven’t even gotten to the crazy price hikes per token that are coming.
Why do you think that?
IMHO, API prices are likely to drop over time as we scale up and efficiencies are found, combined with general pricing pressure from the competition… SOTA models will continue to have SOTA prices, of course, but reasonable priced distilled and open weights models are already common.
A consequence of API prices dropping is that “heavily discounted” consumer plans will also adjust and won’t be so generous relative to API prices.
Some of this seems like wishful thinking to me.
“as we scale up” We already have large data centers, and, if anything, “scaling up” is just driving up expenses for debt and hardware. The real problem with AI, relative to the internet boom, is that the more you use it, the more expensive it is. The economies of scale to be taken advantage of are minimal.
I do think price of compute will come down, but exactly because people will be running their own open source models on their own hardware instead of Sam Altman to stack GPUs in a warehouse, but it will still be too expensive and inaccurate.
And we’re still headed for a financial cliff in this scenario.
Like a fraction of a percent of people will run their own models. It won’t influence price. Remember that coders/tech people are only a minority of users.
Oh, I see. I was mistaken. I thought tech companies were OpenAI’s major customers, and they certainly could make their own data centers for internal work, and that coders–that minority of users–were the only ones likely to pay full price for tokens, the rest of us wouldn´t be willing to pay full fare for a machine that is right most of the time sort of. Thanks for setting me straight on that.
Some large companies do it … but I think you greatly overestimate the willingness of large enterprises to build and maintain their own infra. Once a company has lost the competency (and many have), it’s hard to get it back. There are always pockets of people with the right skillset in a large org, but they mostly don’t want to do DC work anymore. Team/personal servers and beefy laptops, otoh…
Of course they want to turn the corner and ideally keep all their infra, but they might need to restructure their debts if/when the creditors come knocking.
BUT: they have a money printing machine with inference… Enterprise is where most of the money is made, as they pay (closer to) API prices… consumer & small business plans are heavily discounted in comparison, with mostly underutilized use-it-or-lose it plans. They’d be stupid if they were making an opex loss on inference.
As for why API prices are dropping? Competition is a bitch… but they seem willing and able to play the game for now.
If we’re talking about the survivability of AI as a technology, I agree.
If you’re talking about the viability of the hyperscaling business model, I think we are looking at wildly different sets of information.
Because these companies started selling at a loss from the start to get people hooked. Neither Claude nor OpenAI are turning a profit right now.
They were supposed to do their IPO and have positive cash flow already. Time is running out before investors are getting antsy and there’s no more money available for scaling up.
They gobbled up the easy money… now they have to work harder for more, and yeah, they may have to slow down a bit and embrace fiscal responsibility… I expect to see restructuring of debts along the way, but I’d be very surprised to see any of the major US based players implode.
Both Anthropic & OpenAI have debt repayments coming up in 2027 that:
Well then. I stand corrected. The random Internet person with unprecedented access into the books & private financial dealings of two major competitors has an air-tight argument.
I suggest we come back to this thread in a year’s time and see how it is playing out.
Look up some well known critics in the AI space and you will see a bunch of information that aligns with OPs statements. Its always been scheduled for Q2/Q3 2027.