I think it's also important and heavily overlooked to develop and maintain open source "pro" level models. Those that are able to think for 80 minutes and yield heavy solutions.
I'm not an expert in LLMs so it's hard to understand how much are we lacking, is it just the compute and thinking strategies / parallel chains, or something specific architecturally. But I feel there's value there and I haven't seen anything like it available so far.
My guess is that with the new UI they've either mistakenly or deliberately reduced the thinking effort or the budget, even if they write "extended thinking" in the app. And it seems that they're (mistakenly or deliberately) now routing some queries to the Flash model despite the selection of Pro/Thinking.
It was super bad right after launch, yet the AI Studio or API calls were on par to the earlier experience. Despite the selected "extended thinking", for the first time in a very long time the LLM outputed fully incorrect and a non-working code for a super simple problem (schema matching), which it can solve easily (and did through the API). So it's definitely not a coincidence.
I'm hoping that it's temporary, because otherwise we're back to GPT-5.0 levels of bad and it will kill the coding usage.
I would guess it's because ChatGPT Pro allows for 80min "think". I've never had even remotely similar think times with Gemini Deep Think. It's generally around 10-15min for math problems, and get increasingly shorter for continued interactions.
It's not "13 parameters to reason", they just rotated the full 8B parameter space in 13 dimensions and found a rotation that was still able to reason.
Depending on the latent structure, it's possible a nice rotation that would be perfect for some one specific problem, but you still got to search for it, and it's not a guarantee to exist.
But it's a nice step towards LLM parameter-space interpretability.