WMT24++
English-to-55-language translation of WMT24 test data. Scored with automatic metrics such as MetricX or xCOMET.
Cohere added internal Irish, Maltese and Serbian variants.
- Made by
- Released
- February 2025
- Kind
- Translation
- Level
- University
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- All public
- Strongest model tested
-
Qwen3.7-Max #49 on the capability index
- Last in a launch post
- October 2026
- Last model added
- October 2026
In the authors’ words
As large language models (LLM) become more and more capable in languages other than English, it is important to collect benchmark datasets in order to evaluate their multilingual performance, including on tasks like machine translation (MT). In this work, we extend the WMT24 dataset to cover 55 languages by collecting new human-written references and post-edits for 46 new languages and dialects in addition to post-edits of the references in 8 out of 9 languages in the original WMT24 dataset. The dataset covers four domains: literary, news, social, and speech. We benchmark a variety of MT providers and LLMs on the collected dataset using automatic metrics and find that LLMs are the best-performing MT systems in all 55 languages. These results should be confirmed using a human-based evaluation, which we leave for future work.
K-EXAONE leads with 90.5%
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.
- 90.5
K-EXAONE
- 86.7
Nemotron 3 Super
- 86.2
Nemotron 3 Nano 30B-A3B
- 85.8
Hunyuan-MT-7B
- 85.8
Qwen3.7-Max
- 84.8
Nemotron 3.5 Super VL
- 84.4
TranslateGemma 27B
- 84.3
Qwen 3.6 Plus
- 84.1
Nemotron-Cascade 2 30B-A3B
- 83.8
Command A Translate
- 83.7
Nemotron 3 Ultra
- 83.5
TranslateGemma 12B
- 81.0
Command A+
- 80.1
TranslateGemma 4B
- 78.9
Qwen3.5 397B-A17B
- 1
K-EXAONE 90.5%
- 2
Nemotron 3 Super 86.7%
- 3
Nemotron 3 Nano 30B-A3B 86.2%
- 4
Hunyuan-MT-7B 85.8%
- 5
Qwen3.7-Max 85.8%
- 6
Nemotron 3.5 Super VL 84.8%
- 7
TranslateGemma 27B 84.4%
- 8
Qwen 3.6 Plus 84.3%
- 9
Nemotron-Cascade 2 30B-A3B 84.1%
- 10
Command A Translate 83.8%
- 11
Nemotron 3 Ultra 83.7%
- 12
TranslateGemma 12B 83.5%
- 13
Command A+ 81%
- 14
TranslateGemma 4B 80.1%
- 15
Qwen3.5 397B-A17B 78.9%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 90.5% | Dec 2025 | Lab model card | |
| 2 | | 86.7% | Mar 2026 | Lab model card | |
| 3 | | 86.2% | Dec 2025 | Lab model card | |
| 4 | | 85.8% | Sep 2025 | Lab model card | |
| 5 | | 85.8% | May 2026 | Lab model card | |
| 6 | | 84.8% | Oct 2026 | Lab model card | |
| 7 | | 84.4% | Jan 2026 | Lab model card | |
| 8 | | 84.3% | Apr 2026 | Lab model card | |
| 9 | | 84.1% | Mar 2026 | Lab model card | |
| 10 | | 83.8% | Aug 2025 | Lab model card | |
| 11 | | 83.7% | Jun 2026 | Lab model card | |
| 12 | | 83.5% | Jan 2026 | Lab model card | |
| 13 | | 81% | May 2026 | Lab model card | |
| 14 | | 80.1% | Jan 2026 | Lab model card | |
| 15 | | 78.9% | Feb 2026 | Lab model card |
4 models have held number one in labs’ own numbers since its release in February 2025
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Tencent’s own number for Hunyuan-MT-7B passed 85% in September 2025
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
2 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Oct 15, 2026 | 84.8 | WMT24++ (COMET) | |
| Jun 4, 2026 | 83.7 | WMT24++ (en→xx) | |
| Jun 1, 2026 | 84.6 | WMT24++ (XCOMET-XXL, 55 languages) | |
| May 20, 2026 | 81 | WMT24++ (xCOMET-XL) | |
| May 20, 2026 | 85.8 | WMT24++ | |
| Apr 2, 2026 | 84.3 | WMT24++ | |
| Mar 19, 2026 | 84.1 | WMT24++ (en -> xx) | |
| Mar 11, 2026 | 86.7 | WMT24++ (en→xx) | |
| Mar 2, 2026 | 27.2 | WMT24++ | |
| Mar 2, 2026 | 45.8 | WMT24++ | |
| Mar 2, 2026 | 66.6 | WMT24++ | |
| Mar 2, 2026 | 72.6 | WMT24++ | |
| Feb 24, 2026 | 76.3 | WMT24++ | |
| Feb 24, 2026 | 77.6 | WMT24++ | |
| Feb 24, 2026 | 78.3 | WMT24++ (XCOMET-XXL, 55 languages) | |
| Feb 16, 2026 | 78.9 | WMT24++ | |
| Jan 15, 2026 | 80.1 | TranslateGemma 4B, COMET-22, WMT24++ 55-language average | |
| Jan 15, 2026 | 83.5 | TranslateGemma 12B, COMET-22, WMT24++ 55-language average | |
| Jan 15, 2026 | 84.4 | TranslateGemma 27B, COMET-22, WMT24++ 55-language average | |
| Dec 31, 2025 | 90.5 | WMT24++ | |
| Dec 15, 2025 | 86.2 | WMT24++ (en->xx) | |
| Sep 1, 2025 | 85.8 | WMT24pp (XCOMET-XXL) | |
| Aug 28, 2025 | 83.8 | WMT24++ xCometXL, average over 23 languages, English to L2 | |
| Jun 26, 2025 | 50.1 | WMT24++ (ChrF) 0-shot (IT) | |
| Mar 12, 2025 | 55.7 | WMT24++ (ChrF) (PT); IT 0-shot = 53.4 |
19 system cards report it, from 6 labs
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 |
|---|---|---|---|---|
| Oct 23, 2026 | | 74.4 | WMT24++ English to X xCOMET, average of 36 languages, BF16 non-reasoning. chrF 52.5, X to English xCOMET 83.4 (Table 6) | Capabilities |
| Oct 19, 2026 | | 53.4 | WMT24++, chrF++, high. X to eng 55.7, eng to Y 51.0 (Tables 5 and 9) | Capabilities |
| Oct 15, 2026 | | 84.8 | WMT24pp COMET (XCOMET-XXL, en to 9 languages) (Table 10) | Capabilities |
| Sep 12, 2026 | | 80.6 | WMT24++ xCOMET-XL (Table 1 and Section 3.2). Agentic 80.7 | Capabilities |
| Aug 5, 2026 | | WMT24++ per-language EN to XX and XX to EN scores for nine languages, no overall (Table 9) | Capabilities | |
| Jun 9, 2026 | | 83.7 | WMT24++ (en to xx) (Table 10) | Capabilities |
| Apr 9, 2026 | | 91.5 | WMT24++ (ko, de, es, ja, vi), metric not stated (Table 3, Reasoning mode) | Capabilities |
| Mar 19, 2026 | | 84.1 | WMT24++ (en -> xx), XCOMET-XXL, 5 language pairs (Table 1 and A.7) | Capabilities |
| Mar 11, 2026 | | 86.7 | WMT24++ (en to xx) (Table 5) | Capabilities |
| Jan 21, 2026 | | 84.4 | TranslateGemma 27B, COMET-22, WMT24++ 55-language average | Other |
| Jan 5, 2026 | | 90.5 | WMT24++ (ko, de, es, ja, vi), GPT-5-mini judge score 0 to 100 (Table 3, Reasoning mode). Per direction in Table 6. Non-reasoning 88.0 | Capabilities |
| Dec 23, 2025 | | 86.2 | WMT24++ (en to xx) (Table 3) | Capabilities |
| Sep 26, 2025 | | 83.9 | WMT24++ xComet-XL Avg over 23 languages, English to each (Tables 1 and 2). The launch blog prints 83.8 | Capabilities |
| Sep 5, 2025 | | 85.8 | WMT24pp XCOMET-XXL, 29 English-centric pairs (Table 4). CometKiwi 80.61 | Capabilities |
| Jul 15, 2025 | | 90.7 | WMT24++ (ES), EN and ES pair, GPT-4.1 judge score 0 to 100, Non-reasoning only (Table 4) | Capabilities |
| Mar 25, 2025 | | 46.8 | WMT24++, chrF, IT, 0-shot (Table 18) | Capabilities |
| Mar 25, 2025 | | 53.4 | WMT24++, chrF, IT, 0-shot (Table 18) | Capabilities |
| Mar 25, 2025 | | 35.9 | WMT24++, chrF, IT, 0-shot (Table 18) | Capabilities |
| Mar 25, 2025 | | 51.6 | WMT24++, chrF, IT, 0-shot (Table 18) | Capabilities |
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