Swallow - English MT-Bench - Extraction: leaderboard

From the Swallow LLM Leaderboard: English MT-Bench, two-turn dialogues graded by GPT-5.2 against reference answers; 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)85.2#63 (GPT-5.4 (2026-03-05))
2GPT-5 Mini (2025-08-07) (Medium)84.5#175 (GPT-5 Mini (2025-08-07))
3Gemma 3 27B (IT)83.9#528
4GPT-OSS-20B (Medium)83.4#523 (GPT-OSS-20B)
5GPT-4.183.2#258
6Gemma 4 31B (IT) (Thinking)83#178 (Gemma 4 31B (IT))
7GPT-4o (2024-08-06)82.8#343
8ELYZA-Shortcut-1.0-Qwen-32B82.7#560
9GPT-OSS-Swallow-120B-RL-v0.1 (Thinking)82.7#309 (GPT-OSS-Swallow-120B-RL-v0.1)
10gemma-4-26B-A4B-it (Thinking)82.6
11O3 Mini (Medium)82.4#282 (O3 Mini)
12Gemma 4 E4B (IT) (Thinking)82.1
13llm-jp-4-8B-Thinking81.8#529
14O3 (2025-04-16) (Medium)80.8#125 (O3 (2025-04-16))
15llm-jp-4-32B-a3B-Thinking80.5#477

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

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