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Prices have been dropping like a stone over the past two years, due to a combination of new efficiencies being developed for serving plus competition from many vendors: https://simonwillison.net/2024/Dec/31/llms-in-2024/#llm-pric...

I'm not seeing any evidence yet of that trend stopping or reversing.

Training frontier models is expensive. Running inference on them is pretty cheap and for solving the same level of problem, will continue to get cheaper. The more use they get out of a model, the less overhead we need to pay on that inference to subsidize the training.

At the rate they're going it'll just get cheaper. The cost per token continues to drop while the models get better. Hardware is also getting more specialized.

Maybe the current batch of startups will run out of money but the technology itself should only get cheaper.