Also check mine[0], basically random private tests/questions and an ok-ish methodology, testing mostly for general intelligence than coding-specific tasks.
I built it for myself, to test which models to use via OpenRouter for my n8n agents. Currently actually still using gpt-5.3-codex for many things, as its pricing is really good in production (due to how their token caching works).
Gemini models still have the best intelligence (when asked any questions, most likely to get it right), but in production they still have many failure modes[1].
[0]: https://aibenchy.com
Every model release you'll post this, and every time I'll be there to point out how it's completely useless (for reasons you've shared are intentional)
It does things like place the old Gemini 3 Flash above the more capable 3.5 Flash and Opus 4.5 - Opus 4.8 and gpt-5.5
At least, until hopefully one day HN has a rule about accounts that derive 99.9999% of their engagement with the site from shilling a personal project.
Also, what about the major flaw/bias linked for Gemini 3.5 flash? That has major real-life consequences if the model ends up being used for any automated scoring systems.
I found it while trying to use 3.5 Flash for scoring the reasoning of some models, and it gets it wrong because of the centering bias, whereas 3 Flash gets scoring right.
I'm happy you do comment, I did add more coding tests since then and add more improvements (price history per model, displaying cost to run at current pricing, improved scoring).
How is it useless to see that Opus 4.8 is 2x more expensive and 2x slower on some questions?