German LLM Benchmark · Model Profile
Native German named-entity recognition — identify persons, locations, organisations and misc entities in German text, emitted as JSON. Scored with seqeval micro-F1 excluding the noisy MISC class. Run reasoning-off.
via GermEval (via EuroEval) ↗ View run details →Native German exam and licensing questions covering region-specific knowledge — history, law, civics and culture. Written by humans in German, not translated.
via CohereLabs/include-base-44 ↗ View run details →Hard academic questions across 14 subjects — STEM, law, health, economics, philosophy and more. Professionally translated to German, with up to ten answer options per question.
via li-lab/MMLU-ProX ↗Native German social-media sentiment classification — positive, neutral or negative. Human-annotated German text, not translated. Run reasoning-off; headline score is MCC on the predicted label.
via SB10K (via EuroEval) ↗ View run details →Native German linguistic acceptability — does the sentence read as grammatical German (ja / nein)? Built from clean vs. minimally-corrupted German sentences. Run reasoning-off.
via ScaLA-de (via EuroEval) ↗ View run details →