Swallow - Pre-trained English - MMLU: leaderboard
From the Swallow LLM Leaderboard (Institute of Science Tokyo) pre-trained English board, which evaluates base models without post-training. MMLU four-choice exam questions, 5-shot; metric is accuracy (random 25%). 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
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen 2.5 72B | 86.1 | #512 |
| 2 | Qwen 2.5 32B | 83.2 | #544 |
| 3 | Qwen3-30B-A3B-Base | 81.2 | #597 |
| 4 | Qwen3-14B-Base | 80.6 | #628 |
| 5 | Qwen 2.5 14B | 79.7 | #716 |
| 6 | Llama 3.1 70B | 78.6 | #588 |
| 7 | Llama 4 Scout Base | 78 | #708 |
| 8 | gemma-3-27B-pt | 78 | #505 |
| 9 | Qwen3-8B-Base | 76.5 | #626 |
| 10 | Gemma 2 27B | 75.4 | #803 |
| 11 | Qwen 2.5 7B | 74.2 | #895 |
| 12 | gemma-3-12B-pt | 73.7 | #686 |
| 13 | Falcon3-10B-Base | 73.2 | #1187 |
| 14 | Qwen3-4B-Base | 72.9 | #880 |
| 15 | Gemma 2 9B | 70.6 | #924 |
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-mmlu · How It Works · Data refreshed daily, snapshot 2026-11-05.