Swallow - Pre-trained Japanese - XL-Sum: leaderboard

From the Swallow LLM Leaderboard (Institute of Science Tokyo) pre-trained Japanese board, which evaluates base models without post-training. Japanese XL-Sum summarization of BBC news articles, 1-shot; metric is ROUGE-2. Upstream publishes 0-1 scores; shown as 0-100, higher is better.

Metric: ROUGE-2 (%). Source: swallow-llm.github.io. Saturation forecast: Estimated already saturated. 50 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 2.5 72B27.9#512
2Qwen3-14B-Base26.1#628
3Llama 3.1 70B22.8#588
4Qwen 2.5 32B22.8#544
5Qwen 2.5 14B22.5#716
6Qwen3-30B-A3B-Base22.3#597
7Qwen 2.5 7B21.6#895
8gemma-3-27B-pt21#505
9Qwen3-8B-Base20.7#626
10gemma-3-12B-pt19.4#686
11Gemma 2 27B19.4#803
12sarashina2-70B19#586
13Falcon3-10B-Base18.7#1187
14Llama 3.1 8B17.9#1130
15Llama 4 Scout Base17.8#708

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

Interactive version: theaggregate.ai/benchmark?slug=swallow-pre-trained-japanese-xl-sum · How It Works · Data refreshed daily, snapshot 2026-11-05.