I think this might be an unsolved problem. When GPT-5 came out, they had a "router" (classifier?) decide whether to use the thinking model or not.
It was terrible. You could upload 30 pages of financial documents and it would decide "yeah this doesn't require reasoning." They improved it a lot but it still makes mistakes constantly.
I assume something similar is happening in this case.
You're misunderstanding the purpose of "auto"-model-routing or things like "adaptive thinking". It's a solved problem for the companies. It solves their problems. Not yours ;)
Maybe it is an unsolved problem, but either way I am confused why Anthropic is pushing adaptive thinking so hard, making it the only option on their latest models. To combat how unreliable it is, they set thinking effort to "high" by default in the API. In Claude Code, they now set it to "xhigh" by default. The fact that you cannot even inspect the thinking blocks to try and understand its behavior doesn't help. I know they throw around instructions how to enable thinking blocks, or blocks with thinking summaries, or whatever (I am too confused by now, what it is that they allow us to see), but nothing worked for me so far.
I don't think so. If the model used to analyse the complexity is dumb, it won't route correctly. They clearly don't want to start every query using the highest level of intelligence as this could undermine their obvious attempt at resource optimisation.
I faced the same issue using Open Router's intelligent routing mechanism. It was terrible, but it had a tendency to prefer the most expensive model. So 98% of all queries ended up being the most expensive model, even for simple queries.
It makes me think of this parallel: often in combinatorial optimization ,estimating if it is hard to find a solution to a problem costs you as much as solving it.
With a small bounded compute budget, you're going to sometimes make mistakes with your router/thinking switch. Same with speculative decoding, branch predictors etc.
It was terrible. You could upload 30 pages of financial documents and it would decide "yeah this doesn't require reasoning." They improved it a lot but it still makes mistakes constantly.
I assume something similar is happening in this case.