"Opus 4.7 thinks more at higher effort levels, particularly on later turns in agentic settings. This improves its reliability on hard problems, but it does mean it produces more output tokens. "
That's a good point. AA's Cost Efficiency section says the opposite: you can hover to see the breakdown between input, reasoning and output tokens.
I'm not sure where that discrepancy comes from (is Anthropic using different benchmarks?).
There's a few different theories but all we have now are synthetic benchmarks, anecdotes and speculation.
(Benchmarks are misleading, I think our best bet now is for individuals to run real world tests, giving the same task to each model, and compare the quality, cost and time.)
The input cost inflation however is real, and dramatic.
I would have expected them to lower input costs proportionally, because otherwise you're getting less intelligence per dollar even with the smarter model. Think that would be the smartest thing for them to do, at least PR wise. And maybe a bit of free usage as an apology :)
"Opus 4.7 thinks more at higher effort levels, particularly on later turns in agentic settings. This improves its reliability on hard problems, but it does mean it produces more output tokens. "
https://www.anthropic.com/news/claude-opus-4-7