reasoning benchmark
Global-MMLU-Lite Leaderboard
A lightweight version of Global MMLU benchmark that evaluates language models across multiple languages while addressing cultural and linguistic biases in multilingual evaluation.
Updated Aug 17, 2026
Models15
Model coverage15
MetricScore
EvidenceB
Global-MMLU-Lite Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelGO | Score89.2% | Percentile100.0% | Participants15 | EvidenceC | Evaluated |
| Rank02 | ModelGO | Score88.6% | Percentile92.9% | Participants15 | EvidenceC | Evaluated |
| Rank03 | ModelGO | Score88.4% | Percentile85.7% | Participants15 | EvidenceC | Evaluated |
| Rank04 | ModelTM | Score86.7% | Percentile78.6% | Participants15 | EvidenceC | Evaluated |
| Rank05 | ModelGO | Score81.1% | Percentile71.4% | Participants15 | EvidenceC | Evaluated |
| Rank06 | ModelGO | Score78.2% | Percentile64.3% | Participants15 | EvidenceC | Evaluated |
| Rank07 | ModelGO | Score75.1% | Percentile57.1% | Participants15 | EvidenceC | Evaluated |
| Rank08 | ModelGO | Score69.5% | Percentile50.0% | Participants15 | EvidenceC | Evaluated |
| Rank09 | ModelGO | Score69.1% | Percentile42.9% | Participants15 | EvidenceC | Evaluated |
| Rank10 | ModelGO | Score64.5% | Percentile35.7% | Participants15 | EvidenceC | Evaluated |
| Rank11 | ModelGO | Score64.5% | Percentile28.6% | Participants15 | EvidenceC | Evaluated |
| Rank12 | ModelGO | Score59.0% | Percentile21.4% | Participants15 | EvidenceC | Evaluated |
| Rank13 | ModelGO | Score59.0% | Percentile14.3% | Participants15 | EvidenceC | Evaluated |
| Rank14 | ModelGO | Score54.5% | Percentile7.1% | Participants15 | EvidenceC | Evaluated |
| Rank15 | ModelGO | Score34.2% | Percentile0.0% | Participants15 | EvidenceC | Evaluated |
Global-MMLU-Lite Highlights
The leading models and scores on this benchmark.
Global-MMLU-Lite Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for Global-MMLU-Lite
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis global-mmlu-lite 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.
- 01GO
- Score
- 89.2%
- Price
- $1.3 input / $10 output per 1M tokens
- Speed
- Up to 85 tok/s via Google
Strengths
- Ranks #1 of 15 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures Global-MMLU-Lite, not total model capability
- 02GOGemini 2.5 ProGoogle
- Score
- 88.6%
- Price
- $1.3 input / $10 output per 1M tokens
- Speed
- Up to 86 tok/s via Google
Strengths
- Ranks #2 of 15 compared models
- 93th percentile on this benchmark
- C evidence result
Considerations
- This result measures Global-MMLU-Lite, not total model capability
- 03GOGemini 2.5 FlashGoogle
- Score
- 88.4%
- Price
- $0.30 input / $2.5 output per 1M tokens
- Speed
- Up to 85 tok/s via Google
Strengths
- Ranks #3 of 15 compared models
- 86th percentile on this benchmark
- C evidence result
Considerations
- This result measures Global-MMLU-Lite, not total model capability
- 04TMInkling-SmallThinking Machines Lab
- Score
- 86.7%
Strengths
- Ranks #4 of 15 compared models
- 79th percentile on this benchmark
- C evidence result
Considerations
- This result measures Global-MMLU-Lite, not total model capability
- 05GOGemini 2.5 Flash-LiteGoogle
- Score
- 81.1%
- Price
- $0.10 input / $0.40 output per 1M tokens
- Speed
- Up to 5.7 tok/s via Google
Strengths
- Ranks #5 of 15 compared models
- 71th percentile on this benchmark
- C evidence result
Considerations
- This result measures Global-MMLU-Lite, not total model capability
Selection summary
Best AI Models for Global-MMLU-Lite
Gemini 2.5 Pro Preview 06-05 currently leads Global-MMLU-Lite with 89.2%. 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.
What is Global-MMLU-Lite?
What Global-MMLU-Lite measures and how its scores work.
A lightweight version of Global MMLU benchmark that evaluates language models across multiple languages while addressing cultural and linguistic biases in multilingual evaluation.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Global-MMLU-Lite
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- global-mmlu-lite|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Global-MMLU-Lite.
Which model scores highest on Global-MMLU-Lite?
Gemini 2.5 Pro Preview 06-05 is currently ranked first with 89.2%.
What does Global-MMLU-Lite measure?
A lightweight version of Global MMLU benchmark that evaluates language models across multiple languages while addressing cultural and linguistic biases in multilingual evaluation.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
15 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.