[CuriouslyC]

Gemini 2.5 Pro's superiority is IMO largely driven by their long context support and training methodology. Compare Gemini as a beta reader for a 100k token book with GPT4.1 or Claude 4, and it becomes quite clear how much more effectively it can reason across its context than other comparable models. This also makes it much better for architecting new features into a system, since you can load a lot of the current system into the context and it'll conform to existing styles and architecture patterns more closely.

[jacob019]

Agreed, 2.5 flash too. I analyze a large json document of metrics for pricing decisions. Typically around 200k, occtionallly up to 1M, Gemini 2.5 significantly outperforms for my task. It isn't 100%, but role playing gets close. I suppose that's a form of inference time compute.

[t55]

For a 100k token context window; all those models are comparable though

gemini 2.5 pro shines for 200k+ tokens

[CuriouslyC]

I can confirm from first hand experience that even at 100k they are most definitely not comparable for the task of beta reading.

[throwaway314155]

splitting hairs much?