SEA-HELM (Malay): leaderboard

AI Singapore’s SEA-HELM restricted to Malay: the mean over its natural-language understanding, generation, reasoning, instruction-following and cultural tasks in that language. SEA-HELM exists because Southeast Asian languages are where English-first models lose the most, and the per-language boards are where that shows.

Metric: Normalized Score. Source: leaderboard.sea-lion.ai. Saturation forecast: Around January 2027. 58 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.5 122B A10B (Reasoning)76.31#173 (Qwen 3.5 122B A10B)
2Qwen 3.6 27B (Reasoning)76.26#170 (Qwen 3.6 27B)
3Gemma 4 26B A4B (IT) (Reasoning)76.04#297 (Gemma 4 26B A4B (IT))
4Qwen 3.6 35B A3B (Reasoning)75.05#226 (Qwen 3.6 35B A3B)
5Qwen 3.5 27B (Reasoning)74.9#187 (Qwen 3.5 27B)
6Qwen 3.5 35B A3B (Reasoning)74.43#256 (Qwen 3.5 35B A3B)
7Qwen 3 32B (Thinking)71.79#443 (Qwen 3 32B)
8Qwen 3 VL 32B Instruct71.36#283
9Qwen 3.5 9B (Reasoning)71.11#379 (Qwen 3.5 9B)
10Gemma 3 27B (IT)70.16#523
11Llama-SEA-LION-v3-70B-IT70.11#402
12GPT-OSS-120B (Reasoning)69.68#341 (GPT-OSS-120B)
13Llama 3.3 70B Instruct69.23#534
14Llama 4 Scout Instruct68.81#539
15Qwen 3 14B (Reasoning)68.57#537 (Qwen 3 14B)

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

Interactive version: theaggregate.ai/benchmark?slug=sea-helm-malay · How It Works · Data refreshed daily, snapshot 2026-10-20.