If you look at how exponentially cheaper individual units of work have become over the last few years there’s no real reason to worry about price gouging. Particularly when there’s still competition in the market, and open-source models.
Without those you’d have a point.
Im in a combined coding and marketing role so for me its a huge time saver. Far from perfect, but so am I.
Have any of the AI companies ever reduce their input output token prices I’ve always been under the impressive gone up. Not that I keep much of an eye on it.
You’re talking about the cost to the consumer, where I was talking about the energy cost of an individual unit of work by a given model, but they’re both relevant. The underlying energy cost of generating a token at a given level of capability has been falling as hardware and inference become more efficient. Those efficiency gains can feed through into lower token prices for users, but also a more capable model can often complete the same task with fewer tokens, fewer retries and less prompting.
So even if the headline price of a new frontier model looks similar or higher, the actual cost, both in energy and money, of getting a given piece of work done can still fall substantially. It’ll keep doing so too, its still in its infancy.
If you look at how exponentially cheaper individual units of work have become over the last few years there’s no real reason to worry about price gouging. Particularly when there’s still competition in the market, and open-source models.
Without those you’d have a point.
Im in a combined coding and marketing role so for me its a huge time saver. Far from perfect, but so am I.
Have any of the AI companies ever reduce their input output token prices I’ve always been under the impressive gone up. Not that I keep much of an eye on it.
The chinese models are getting cheaper now that they have “flash” variants
You’re talking about the cost to the consumer, where I was talking about the energy cost of an individual unit of work by a given model, but they’re both relevant. The underlying energy cost of generating a token at a given level of capability has been falling as hardware and inference become more efficient. Those efficiency gains can feed through into lower token prices for users, but also a more capable model can often complete the same task with fewer tokens, fewer retries and less prompting.
So even if the headline price of a new frontier model looks similar or higher, the actual cost, both in energy and money, of getting a given piece of work done can still fall substantially. It’ll keep doing so too, its still in its infancy.