Swallow - Japanese MT-Bench - Extraction: 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. This board covers the Extraction category: extracting entities, numbers and sentiment from text.

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)78.7#63 (GPT-5.4 (2026-03-05))
2GPT-4o (2024-08-06)77.6#343
3O3 Mini (Medium)77.4#282 (O3 Mini)
4gemma-4-26B-A4B-it (Thinking)77.2
5GPT-5 Mini (2025-08-07) (Medium)77#175 (GPT-5 Mini (2025-08-07))
6Qwen3-Swallow-32B-RL-v0.2 (Thinking)76.8#374 (Qwen3-Swallow-32B-RL-v0.2)
7Qwen 3 32B (Thinking)76.5#449 (Qwen 3 32B)
8Gemma 3 27B (IT)76.4#528
9O3 (2025-04-16) (Medium)76.4#125 (O3 (2025-04-16))
10GPT-OSS-Swallow-120B-RL-v0.1 (Thinking)76.3#309 (GPT-OSS-Swallow-120B-RL-v0.1)
11GPT-5 (Medium)75.8#105 (GPT-5)
12GPT-4.175.7#258
13Gemma 4 31B (IT) (Thinking)75.7#178 (Gemma 4 31B (IT))
14llm-jp-4-32B-a3B-Thinking75#477
15GPT-OSS-20B (Medium)74.9#523 (GPT-OSS-20B)

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