Swallow - Pre-trained English - XWINO: leaderboard

From the Swallow LLM Leaderboard (Institute of Science Tokyo) pre-trained English board, which evaluates base models without post-training. English XWinograd two-choice pronoun resolution, 4-shot; metric is accuracy (random 50%). 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
1gemma-3-27B-pt92.3#505
2Gemma 2 27B92.1#803
3Llama 3.1 70B92#588
4gemma-3-12B-pt91.7#686
5sarashina2-70B91.7#586
6Qwen 2.5 32B91.3#544
7Llama 3.1 8B90.7#1130
8Gemma 2 9B90.7#924
9Qwen3-8B-Base90.3#626
10llm-jp-3-13B90.2#1176
11Qwen 2.5 72B90.1#512
12Falcon3-10B-Base90.1#1187
13Qwen3-14B-Base90.1#628
14Qwen3-30B-A3B-Base90.1#597
15Qwen 2.5 14B89.9#716

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