"It costs OpenAI less money to serve GPT-5.5 than GPT-4." does it though? do you have the numbers? Or you just making stuff up?
It would be more surprising if the surrounding architecture hasn't significantly diverged. If it _hasn't_ significantly diverged, then given the performance difference it would imply that the frontier models have significantly greater param counts, which would result in a higher cost.
We also have to assume that these operators are correctly pricing GPU depreciation, and the market is so new there is no reason to believe they are.
Input: $30 / 1M tokens
Output: $60 / 1M tokens
GPT-5.5:
Input: $5 / 1M tokens
Output: $30 / 1M tokens
Costs have been reducing by over 5x year over year. Inference cost concern is mostly performative.
https://simianwords.bearblog.dev/conclusive-proofs-that-llm-...
Edit: can't reply but companies aren't selling inference at loss. In the blog post I point to third party hosting of open models like Deepseek which are also going down. They are not VC backed.
I also point to Gemma 31B which you can run on your laptop today that beats most models from 2024.
We will only know the actually situation once Anthropic goes public and we can look at their books.
That blog post is not very compelling either. Without knowing details of the architecture, comparing the various frontier models to open models doesn’t make sense.
Why do you need to know the architecture? Just compare Deepseek V4's performance with GPT 4 and treat internals as a blackbox. Deepseek is much cheaper and way more performant. If you can agree to reasonable assumptions
1. that closed source models are more efficient than open source
2. Deepseek is served at a profit and not a loss
Then it is pretty clear that the prices have gone down. If the prices have gone down more than 20x-30x then surely it is not _still_ subsidised is it?
I think this amount of skepticism is not warranted here. Every reasonable explanation or proxy is met with "but you don't know what they really do" is naive.
It is borderline conspiratorial to believe it this way.
Not a reasonable assumption for a variety of reasons.
> 2. Deepseek is served at a profit and not a loss
Not a reasonable assumption either.
> Why do you need to know the architecture? Just compare Deepseek V4's performance with GPT 4 and treat internals as a blackbox.
Because the internals are what actually matter and what drives inference cost.
It would be entirely reasonable to expect that GPT-5.5 has some sort of optimizations or changes to the architecture to make it easier to train, or to make runtime ablation easier, or to better handle large batches, or whatever.
Those changes, particularly if they are non-public, can easily result in worse inference performance than a comparably sized model without those changes.
> It is borderline conspiratorial to believe it this way.
It's not any sort of conspiracy. It's how land-grab tech companies have always worked. To presume otherwise is silly.
Pricing has no correlation with profit. It can be artificially lowered to kill competition, and artificially inflated to maximize profit.
GPT-4.1 Input: $2.00 / 1M Tokens Output: $8.00 / 1M Tokens