Swallow - Pre-trained Japanese - JCommonsenseQA: leaderboard

From the Swallow LLM Leaderboard (Institute of Science Tokyo) pre-trained Japanese board, which evaluates base models without post-training. JCommonsenseQA five-choice commonsense questions built from a knowledge base (JGLUE), 4-shot; metric is accuracy (random 20%). Upstream publishes 0-1 scores; shown as 0-100, higher is better.

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

Top models

#ModelScoreOverall rank
1Qwen 2.5 72B97.2#512
2Qwen 2.5 32B96.1#544
3Llama 4 Scout Base95.8#708
4Qwen 2.5 14B95.8#716
5Qwen3-14B-Base95.6#628
6Llama 3.1 70B94.6#588
7gemma-3-27B-pt94.4#505
8Gemma 2 27B93.6#803
9sarashina2-70B92.9#586
10Qwen3-8B-Base92.7#626
11Qwen3-30B-A3B-Base92.7#597
12Qwen 2.5 7B92.4#895
13sarashina2.2-3B91.1#766
14Qwen3-4B-Base91#880
15plamo-2-8B90.9#839

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