BALSAM - Factuality: leaderboard

BALSAM Arabic benchmark (SDAIA/KSAA, dataset version 2), Factuality category: judging the factual correctness of claims and answers against a provided text. The category has only multiple-choice tasks, so the site's overall score is 30% of the LLM-judged multiple-choice score and cannot exceed 30; higher is better.

Metric: Overall score (0-100, LLM-judged generation and multiple choice). Source: benchmarks.ksaa.gov.sa. Saturation forecast: Around February 2027. 38 models tracked.

Top models

#ModelScoreOverall rank
1Command A 03 202526.56#530
2Qwen 3 235B A22B25.67#323
3GLM-5 (Thinking)25.44#149 (GLM-5)
4GLM-4.7 (Reasoning)25.44#202 (GLM-4.7)
5Jais-2-70B-Chat25.44#430
6DeepSeek V3.224.78#210
7GPT-5.224.55#115
8Nova Pro (v1)24.33#508
9Claude Opus 4.523.11#87
10Fanar-C-2-27B22.11#637
11Command-R+21#869
12Llama 4 Maverick Instruct20.89#467
13Kimi K2 Instruct (0905)20.89#267
14GPT-OSS-120B (Reasoning)20.67#346 (GPT-OSS-120B)
15Yehia-7B-preview20.33#659

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=balsam-factuality · How It Works · Data refreshed daily, snapshot 2026-11-05.