WMT25 Terminology Translation Task
North Small Translate 1.0 89.7% Only in system cards 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 2025-06-24 with two tracks. 21 systems from 15 teams took part. Cohere reports corpus-level terminology success rate.
- Level
- Expert Specialists with years of training, often over hours of work
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Open-ended Free-form text, documents, designs or media judged as a whole.
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.
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | North Small Translate 1.0 | 89.7% | Sep 2026 | Model card |
The best score passed 85% in Sep 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 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 |
|---|---|---|---|---|
| 12 Sep 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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