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language benchmark

WMT23 Leaderboard

The Eighth Conference on Machine Translation (WMT23) benchmark evaluating machine translation systems across 8 language pairs (14 translation directions) including general, biomedical, literary, and low-resource language translation tasks. Features specialized shared tasks for quality estimation, metrics evaluation, sign language translation, and discourse-level literary translation with professional human assessment.

Updated Aug 17, 2026

Models4
Model coverage4
MetricScore
EvidenceB

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  • FAQ

WMT23 Ranking

Higher score ranks better on this benchmark.

4 rows
Columns

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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelGOGemini 1.5 ProGoogleScore75.1%Percentile100.0%Participants4EvidenceCEvaluatedAug 17, 2026
Rank02ModelGOGemini 1.5 FlashGoogleScore74.1%Percentile66.7%Participants4EvidenceCEvaluatedAug 17, 2026
Rank03ModelGOGemini 1.5 Flash 8BGoogleScore72.6%Percentile33.3%Participants4EvidenceCEvaluatedAug 17, 2026
Rank04ModelGOGemini 1.0 ProGoogleScore71.7%Percentile0.0%Participants4EvidenceBEvaluatedAug 17, 2026

WMT23 Highlights

The leading models and scores on this benchmark.

Rank #1Gemini 1.5 Pro75.1%Rank #2Gemini 1.5 Flash74.1%Rank #3Gemini 1.5 Flash 8B72.6%Rank #4Gemini 1.0 Pro71.7%

WMT23 Score Distribution

A closer view of the leading scores on this benchmark.

WMT23

The Top AI Models for WMT23

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

Ranking basisThis wmt23 AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    GO
    Gemini 1.5 ProGoogle
    Score
    75.1%
    Speed
    Up to 85 tok/s via Google

    Strengths

    • Ranks #1 of 4 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures WMT23, not total model capability
  2. 02
    GO
    Gemini 1.5 FlashGoogle
    Score
    74.1%
    Speed
    Up to 150 tok/s via Google

    Strengths

    • Ranks #2 of 4 compared models
    • 67th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures WMT23, not total model capability
  3. 03
    GO
    Gemini 1.5 Flash 8BGoogle
    Score
    72.6%
    Speed
    Up to 150 tok/s via Google

    Strengths

    • Ranks #3 of 4 compared models
    • 33th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures WMT23, not total model capability
  4. 04
    GO
    Gemini 1.0 ProGoogle
    Score
    71.7%
    Speed
    Up to 120 tok/s via Google

    Strengths

    • Ranks #4 of 4 compared models
    • 0th percentile on this benchmark
    • B evidence result

    Considerations

    • This result measures WMT23, not total model capability

Selection summary

Best AI Models for WMT23

Gemini 1.5 Pro currently leads WMT23 with 75.1%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.

Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.

Benchmark rank #1Gemini 1.5 Pro75.1% · Up to 85 tok/s via GoogleBenchmark rank #2Gemini 1.5 Flash74.1% · Up to 150 tok/s via GoogleBenchmark rank #3Gemini 1.5 Flash 8B72.6% · Up to 150 tok/s via Google

What is WMT23?

What WMT23 measures and how its scores work.

The Eighth Conference on Machine Translation (WMT23) benchmark evaluating machine translation systems across 8 language pairs (14 translation directions) including general, biomedical, literary, and low-resource language translation tasks. Features specialized shared tasks for quality estimation, metrics evaluation, sign language translation, and discourse-level literary translation with professional human assessment.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
WMT23
Modality
text
Primary category
language
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
wmt23|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about WMT23.

Which model scores highest on WMT23?

Gemini 1.5 Pro is currently ranked first with 75.1%.

What does WMT23 measure?

The Eighth Conference on Machine Translation (WMT23) benchmark evaluating machine translation systems across 8 language pairs (14 translation directions) including general, biomedical, literary, and low-resource language translation tasks. Features specialized shared tasks for quality estimation, metrics evaluation, sign language translation, and discourse-level literary translation with professional human assessment.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

4 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.