bert-large-nordic-pile-1M-steps: benchmark results

AI Sweden's 24-layer BERT-large masked-language encoder, trained on the Swedish subset of the Nordic Pile using a Wafer-Scale Engine. It is an encoder checkpoint for masked-token prediction and downstream adaptation, distinct from the autoregressive GPT-SW3 releases. Provider: AI Sweden. Access: Open.

Aggregate Rating 1478 ± 39, rank #2694 of 10916 rated models, from 27 benchmark results.

Strongest benchmark results

BenchmarkScoreMetricPercentile
EuroEval Swedish76.25Average Score (%)99.3
EuroEval Swedish NLU76.25NLU Average Score (%)99.3
EuroEval Swedish NLU - SUC379.99Micro F1 excluding MISC (%)98
EuroEval Swedish NLU - ScaLA SV72.07Matthews correlation coefficient (%)97.8
EuroEval Norwegian NLU - NorNE NB85.74Micro F1 excluding MISC (%)96.2
EuroEval Faroese NLU - FONE82.96Micro F1 excluding MISC (%)94.8
EuroEval Icelandic NLU - MIM-GOLD NER64.07Micro F1 excluding MISC (%)79.5
EuroEval Danish NLU - Dansk62.1Micro F1 excluding MISC (%)78
EuroEval Swedish NLU - Swerec76.69Matthews correlation coefficient (%)67.7
EuroEval Norwegian44.23Average Score (%)61.3
EuroEval Icelandic30.79Average Score (%)59
EuroEval Danish NLU - ScaLA DA34.29Matthews correlation coefficient (%)56.4

Interactive version: theaggregate.ai/model?slug=bert-large-nordic-pile-1m-steps · How It Works · Data refreshed daily, snapshot 2026-11-08.