How is everyone monitoring the skill/utility of all these different models? I am overwhelmed by how many they are, and the challenge of monitoring their capability across so many different modalities.

https://www.swebench.com

https://swe-rebench.com

https://livebench.ai/#/

https://eqbench.com/#

https://contextarena.ai/?needles=8

https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com...

https://artificialanalysis.ai/leaderboards/models

https://gorilla.cs.berkeley.edu/leaderboard.html

https://github.com/lechmazur/confabulations

https://dubesor.de/benchtable

https://help.kagi.com/kagi/ai/llm-benchmark.html

https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard

This is the best summary, in my opinion. You can also see the individual scores on the benchmarks they use to compute their overall scores.

It's nice and simple in the overview mode though. Breaks it down into an intelligence ranking, a coding ranking, and an agentic ranking.

https://artificialanalysis.ai/