Swallow - Japanese MT-Bench - Average: leaderboard

From the Swallow LLM Leaderboard: Japanese MT-Bench (Nejumi edition, v4 questions with corrected v2 reference answers), two-turn dialogues graded by GPT-5.2 against references; normalized 0-1 upstream, shown as 0-100, higher is better. Mean over the eight question categories, for post-trained models.

Metric: Judge Score (normalized, %). Source: swallow-llm.github.io. Saturation forecast: Estimated already saturated. 68 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.4 (2026-03-05) (Medium)84.4#63 (GPT-5.4 (2026-03-05))
2GPT-5 (Medium)84.2#105 (GPT-5)
3GPT-5 Mini (2025-08-07) (Medium)83#175 (GPT-5 Mini (2025-08-07))
4O3 (2025-04-16) (Medium)81.8#125 (O3 (2025-04-16))
5Gemma 4 31B (IT) (Thinking)81.5#178 (Gemma 4 31B (IT))
6gemma-4-26B-A4B-it (Thinking)80.6
7Qwen 3.5 27B (Thinking)78.4#192 (Qwen 3.5 27B)
8O3 Mini (Medium)78.2#282 (O3 Mini)
9Qwen 3 235B A22B 2507 Instruct77.9#315
10Qwen 3.5 122B A10B (Thinking)77.8#184 (Qwen 3.5 122B A10B)
11GPT-OSS-Swallow-120B-RL-v0.1 (Thinking)77.2#309 (GPT-OSS-Swallow-120B-RL-v0.1)
12GPT-4.177.1#258
13Qwen 3.5 35B A3B (Thinking)76#268 (Qwen 3.5 35B A3B)
14Qwen 3 Next 80B A3B (Thinking)75.9#312
15Gemma 4 E4B (IT) (Thinking)75.8

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

Interactive version: theaggregate.ai/benchmark?slug=swallow-japanese-mt-bench-average · How It Works · Data refreshed daily, snapshot 2026-11-05.