Swallow - Pre-trained Japanese - Average: leaderboard

From the Swallow LLM Leaderboard (Institute of Science Tokyo) pre-trained Japanese board, which evaluates base models without post-training. Unweighted mean of JCommonsenseQA, JEMHopQA, NIILC, JSQuAD, XL-Sum, MGSM, WMT20 En-Ja and Ja-En, JMMLU and JHumanEval. Upstream publishes 0-1 scores; shown as 0-100, higher is better.

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

Top models

#ModelScoreOverall rank
1Qwen 2.5 72B62.3#512
2Qwen 2.5 32B59.1#544
3Qwen3-14B-Base59.1#628
4Qwen3-30B-A3B-Base58#597
5gemma-3-27B-pt57.4#505
6Qwen 2.5 14B56.8#716
7Llama 3.1 70B56.6#588
8Llama 4 Scout Base56.5#708
9Qwen3-8B-Base55.1#626
10Gemma 2 27B54.6#803
11sarashina2-70B53#586
12gemma-3-12B-pt51.8#686
13sarashina2.2-3B51.6#766
14Qwen 2.5 7B51.2#895
15Qwen3-4B-Base51.1#880

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-average · How It Works · Data refreshed daily, snapshot 2026-11-05.