WMT25 Terminology Translation Task
Models translate sentence, paragraph and document level text with a supplied source to target glossary. Scoring checks quality and whether the prescribed target terms appear.
Test data came out on June 24th, 2025 with two tracks. 21 systems from 15 teams took part. Cohere reports corpus-level terminology success rate.
- Released
- June 2025
- Kind
- Translation
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Open-ended
- Tasks
- All public
- Last in a system card
- September 2026
- Last model added
- September 2026
North Small Translate 1.0 leads with 89.7%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 |  North Small Translate 1.0 | 89.7% | Sep 2026 | Lab model card |
Cohere’s own number for North Small Translate 1.0 passed 85% in September 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs report it only in system cards
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Sep 12, 2026 | North Small Translate 1.0 technical report | 89.7 | Terminology, WMT25 Terminology Translation Task, corpus-level terminology success rate, 5 directions (Table 1 and Section 3.4). Agentic 87.9 | Capabilities |
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