Featuring Every Eval Ever Results on Hugging Face Model Pages

Two platforms for reporting AI model evaluation results are now compatible with each other. Every Eval Ever, a standardized system for recording evaluation results launched by a cross-institutional coalition, can now share data with Hugging Face Community Evals, which displays benchmark scores on model pages across the Hub. The compatibility matters because evaluation results are currently scattered across papers, leaderboards, and blog posts in different formats, making it difficult for users and researchers to compare models or understand why the same model sometimes shows different scores on the same benchmark. The integration uses a converter that transforms Every Eval Ever records into the format Hugging Face expects, allowing a single evaluation to appear both on model pages with a link to its full source record and in a standardized metadata store that researchers and policymakers can access.