AI benchmark / Multimodal evaluation
A crowdsourced benchmark that asks users to upload photos without obvious toilet signs and label where they would go to find the restroom, aiming to test whether AI can handle this kind of real-world visual inference.
The page clearly presents an AI-related benchmark project with a specific task, a visible upload flow, privacy guidance, and a concrete evaluation goal. It is distinct enough for a public listing because it focuses on multimodal reasoning in a narrow real-world scenario, and the page shows enough evidence that users can contribute data directly.
The crawl does not show the benchmark format beyond photo collection, such as how labels are used, whether there is an actual model evaluation leaderboard, or any dataset size, examples, or results.
Last evaluated 9 hours ago. Current rank #2432. Down 1 spot in the rankings.
A GitHub repo benchmarking TypeSafe’s Jev against Sonnet, GPT-5 nano, and local models on 770 Reddit AITA verdicts, with Brier scores, latency, and cost comparisons.
A benchmark for testing whether coding agents can show staff-level engineering judgment, not just produce correct code.
An AI strategy benchmark that pits frontier language models against each other in turn-based games and records decision logs and raw replays.
