Very interesting. For my use cases, Gemini's responses beat Sonnet 3.7's like 80% of the time (gut feeling, didn't collect actual data). It beats Sonnet 100% of the time when the context gets above 120k.
As usual with LLMs. In my experience, all those metrics are useful mainly to tell which models are definitely bad, but doesn't tell you much about which ones are good, and especially not how the good ones stack against each other in real world use cases.
Andrej Karpathy famously quipped that he only trusts two LLM evals: Chatbot Arena (which has humans blindly compare and score responses), and the r/LocalLLaMA comment section.
Okay, it's common across other industries, but not this one. Here is Google, Facebook, and Anthropic comparing their frontier models to others[1][2][3].
Confusing take - Gemini 2.5 is probably the best general purpose coding model right now, and before that it was Sonnet 3.5. (Maybe 3.7 if you can get it to be less reward-hacky.) OpenAI hasn't had the best coding model for... coming up on a year, now? (o1-pro probably "outperformed" Sonnet 3.5 but you'd be waiting 10 minutes for a response, so.)
Who has a (publicly released) model that is SOTA is constantly changing. It’s more interesting to see who is driving the innovation in the field, and right now that is pretty clearly OpenAI (GPT-3, first multi-modal model, first reasoning model, ect).
