ThaiSafetyBench - Malicious Uses: leaderboard

ThaiSafetyBench (SCB DataX and SCB 10X, 2026) sends 1,954 harmful prompts written in Thai to each model and judges the responses with GPT-4.1 and Gemini 2.5 Pro; the attack success rate is averaged over both judges. This board covers the prompts in its malicious uses category. Metric is attack success rate (%), lower is better (safer).

Metric: Attack Success Rate (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 24 models tracked.

Top models

#ModelScoreOverall rank
1GPT-51.06#105
2Claude Sonnet 4.54.39#148
3SeaLLMs-v3-7B-Chat6.8#897
4Qwen 2.5 72B Instruct8.61#469
5GPT-4o9.67#357
6Gemma 3 12B (IT)10.27#672
7Llama-SEA-LION-v3-8B-IT10.29#800
8Qwen 2.5 7B Instruct10.88#863
9Llama-SEA-LION-v3-70B-IT11.48#407
10Llama 3.3 70B Instruct13.44#541
11Gemma 3 4B (IT)17.54#997
12Llama 3.1 8B Instruct25.08#1017
13Llama 3.1 70B Instruct25.57#567
14Llama 3.2 3B Instruct28.1#1327
15Llama 3.2 1B Instruct41.09#1518

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

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