Open Japanese LLM - Xlsum JA RougeLsum: leaderboard
The "Xlsum JA RougeLsum" subtask of Open Japanese LLM. A task from the Open Japanese LLM Leaderboard, evaluating models on Japanese-language knowledge, reasoning and understanding.
Metric: Score (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 418 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Llama-3.1-Tulu-3-70B | 39.7 | #482 |
| 2 | aya-expanse-32B | 30.25 | #692 |
| 3 | Gemma 2 27B (IT) | 29.95 | #645 |
| 4 | Qwen 1.5 32B | 29.87 | #794 |
| 5 | Gemma 2 9B (IT) | 29.74 | #788 |
| 6 | aya-23-35B | 29.01 | #883 |
| 7 | Qwen 2 57B A14B | 28.16 | #783 |
| 8 | Qwen 2.5 32B | 27.4 | #546 |
| 9 | Linkbricks-Horizon-AI-Korean-Superb-22B | 26.79 | #708 |
| 10 | granite-3.1-2B-instruct | 26.48 | #1385 |
| 11 | llm-jp-3.1-13B-instruct4 | 26.34 | #835 |
| 12 | Qwen 2 7B | 26.22 | #1095 |
| 13 | aya-23-8B | 26.03 | #1299 |
| 14 | Mistral Nemo Instruct (2407) | 25.82 | #936 |
| 15 | Qwen 2.5 14B | 25.54 | #725 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=open-japanese-llm-xlsum-ja-rougelsum · How It Works · Data refreshed daily, snapshot 2026-10-20.