EEE (Every Eval Ever) was born in February 2026 as an inter-institutional effort to fix a very prosaic problem: model evaluation results are everywhere and in every format. What’s the effect? Hard comparisons, lack of traceability, and distrust when the same benchmarks return different numbers depending on who ran them. Sound familiar?

Qué es EEE y por qué importa

EEE proposes a solution that’s both simple and technical: a single JSON schema for each evaluation result that records essential data. What does it store exactly? Who ran the evaluation, which model was evaluated, how the model was accessed, the generation configuration, what the metric means and, optionally, a JSONL file with per-sample outputs.

That changes how reporting works. Instead of scores scattered across papers, harness logs, leaderboards and posts, everything ends up in the same structure. Since its launch EEE has fed a datastore on Hugging Face with ~229000 evaluation results, covering over 22000 models and 2200 benchmarks, extracted from 31 different formats. Reproducing just those runs from scratch would cost hundreds of thousands of dollars, so keeping traceability is also cost-efficient.