MultiNRC
A native (non-translated) multilingual reasoning benchmark of 1,000+ questions written by native speakers in French, Spanish, and Chinese across four categories (language-specific linguistic reasoning, wordplay/riddles, cultural/tradition reasoning, and culturally relevant math), scoring LLMs on accuracy.
What this benchmark measures
A native (non-translated) multilingual reasoning benchmark of 1,000+ questions written by native speakers in French, Spanish, and Chinese across four categories (language-specific linguistic reasoning, wordplay/riddles, cultural/tradition reasoning, and culturally relevant math), scoring LLMs on accuracy.
Rows on this page are sourced from public benchmark artifacts, leaderboard exports, or source-linked model reports. Each row keeps benchmark version, source model name, and available run details attached to the score.
The metric shown here is accuracy. It should be interpreted within MultiNRC, not compared as part of a site-wide ranking.
Frequently asked
What is MultiNRC?
A native (non-translated) multilingual reasoning benchmark of 1,000+ questions written by native speakers in French, Spanish, and Chinese across four categories (language-specific linguistic reasoning, wordplay/riddles, cultural/tradition reasoning, and culturally relevant math), scoring LLMs on accuracy. It is a reasoning benchmark measured by accuracy.
What does accuracy mean on MultiNRC?
MultiNRC reports accuracy (%); higher is better. Scores are shown only within MultiNRC and are never averaged with other benchmarks.
What is the top reported MultiNRC score?
Gemini 3.1 Pro Preview has the top reported score on MultiNRC: 64.74% (accuracy).
Why do MultiNRC scores differ across runs?
Harness, scaffold, reasoning effort, and prompt setup change results, so two runs of the same model can differ. evals.report keeps each score with its run context so the differences stay visible.
Does evals.report rank models across benchmarks?
No. MultiNRC scores are shown within their own metric; evals.report never combines benchmarks into a composite ranking or a single "best model".