What methodology would you propose given the available information?
1. Increased revenue normally means increased usage. [We don't dispute that, right?]
2. Increased usage normally means increased cost.
3. There is an exception to 2: if Anthropic made a gigantic discovery and was able to reduce the cost while increasing the usage - but since it would be in their best interests, they would announce this information and brag about it for months, but they haven't (what they do is just playing the quantization game all labs do, but this is beside the point).
4. Hence, we have very solid reasons to assume their costs increased.
"Opus 5.5 requires less compute to serve than Opus 5, and its pricing reflects that. Our tests show that at default settings it will cost 40% less than Opus 5 on typical workloads."
https://www.anthropic.com/claude-sonnet-5-5
"Sonnet 5.5 requires fewer tokens per task than Sonnet 5, so it’s less expensive to run. It also generates output 30%+ faster"
OpenAI have been achieving even more impressive optimizations, hence why GPT-6 Sol and GPT-6 Luna are half the price of their 5.6 equivalents.