LiT (Lost in Translation) Robustness - Idioms and Cultural Metaphors: leaderboard

Metric: MQM>=80 rate (%): share of round-trip translations whose back-translation to English scores at least 80 on an MQM error scale (minor -1, major -5, critical -25) from a Grok 4.1 Fast judge comparing it with the English source; each passage is translated serially through a four-language sequence and back, averaged over eight sequences (high, medium and low-resource languages); robustness subset: idioms and cultural metaphors; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 22 models tracked.

Top models

#ModelScore
1Qwen 3.5 397B A17B62.5
2GLM-554.2
3Kimi K2 (Thinking)49
4Gemma 4 31B (IT) (Thinking)47.9
5Gemma 4 31B (IT)44.8
6GLM-4.743.8
7Qwen 3 235B A22B 2507 (Thinking)42.7
8Qwen 3.5 35B A3B40.6
9Qwen 3.5 397B A17B (Non-reasoning)38.5
10GPT-OSS-120B (High)37.5
11DeepSeek V3.2 Exp (Non-reasoning)34.4
12MiniMax-M2.533.3
13Gemma 3 27B (IT)31.2
14DeepSeek V3.2 Exp (Thinking)29.2
15Qwen 3 235B A22B 2507 Instruct26

Interactive version: theaggregate.ai/benchmark?slug=lit-lost-in-translation-robustness-idioms-and-cultural-metaphors · How It Works · Data refreshed daily, snapshot 2026-10-07.