BloomBench - Arabic - Evaluate: leaderboard

BloomBench (Almieyar-Oryx series, QCRI, 2026) is a bilingual English and Arabic multiple-choice benchmark for vision-language models organized by the six levels of the revised Bloom taxonomy, scored as zero-shot accuracy in percent from the answer letter parsed from generated text (chance 25). This board is accuracy on the 592 Modern Standard Arabic items of the Evaluate level (judging logical coherence, harm and safety, and image quality); higher is better.

Metric: Accuracy (%) on the 592 Arabic BloomBench items at the Bloom level Evaluate (judging coherence, harm and safety, and image quality), four-option image-question multiple choice, zero-shot, temperature 0, the chosen letter parsed from the generated answer (Regex-based Answer Extraction; unparseable answers count as wrong); chance 25; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 8 models tracked.

Top models

#ModelScoreOverall rank
1Gemma 4 31B93#394
2Gemma 3 27B89#1631
3Gemma 4 26B A4B89#615
4Gemma 3 12B88#2000
5GPT-4o Mini83#1623
6Qwen 2.5 VL 7B82#1787
7Qwen 2 VL 7B79#2261
8Gemma 3 4B73#5064

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=bloombench-arabic-evaluate · How It Works · Data refreshed daily, snapshot 2026-11-13.