SEA-HELM (Malay) - SEA-NLI: leaderboard
SEA-NLI: natural language inference items that SEA-HELM groups under its cultural competency for Malay. Normalized 0-100 score from AI Singapore's SEA-HELM leaderboard: (score - random baseline) / (maximum - baseline), floored at 0 and averaged over eight runs; higher is better.
Metric: Normalized Score. Source: leaderboard.sea-lion.ai. Saturation forecast: Around February 2027. 58 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen 3.6 27B (Reasoning) | 71.14 | #182 (Qwen 3.6 27B) |
| 2 | Gemma 4 26B A4B (IT) (Reasoning) | 66.8 | #293 (Gemma 4 26B A4B (IT)) |
| 3 | Qwen 3.6 35B A3B (Reasoning) | 65.07 | #238 (Qwen 3.6 35B A3B) |
| 4 | Qwen 3.5 122B A10B (Reasoning) | 64.19 | #184 (Qwen 3.5 122B A10B) |
| 5 | Qwen 3 VL 32B Instruct | 62.91 | #290 |
| 6 | Llama 4 Scout Instruct | 62.8 | #547 |
| 7 | Qwen 3.5 27B (Reasoning) | 62.73 | #192 (Qwen 3.5 27B) |
| 8 | Gemma 3 27B (IT) | 61.54 | #528 |
| 9 | Qwen 3 VL 8B Instruct | 60.26 | #419 |
| 10 | Qwen 3 VL 4B Instruct | 59.84 | #510 |
| 11 | Llama 3.3 70B Instruct | 59.68 | #541 |
| 12 | Qwen 3 32B (Thinking) | 59.06 | #449 (Qwen 3 32B) |
| 13 | Qwen 3.5 35B A3B (Reasoning) | 58.69 | #268 (Qwen 3.5 35B A3B) |
| 14 | Llama-SEA-LION-v3-8B-IT | 57.17 | #800 |
| 15 | Llama-SEA-LION-v3-70B-IT | 56.84 | #407 |
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-sea-nli · How It Works · Data refreshed daily, snapshot 2026-11-05.