math benchmark
MMVetGPT4Turbo Leaderboard
MM-Vet evaluation using GPT-4 Turbo for scoring. This variant of MM-Vet examines large multimodal models on complicated multimodal tasks requiring integrated capabilities across six core vision-language abilities: recognition, knowledge, spatial awareness, language generation, OCR, and math.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
MMVetGPT4Turbo Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score74.0% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
MMVetGPT4Turbo Highlights
The leading models and scores on this benchmark.
The Top AI Models for MMVetGPT4Turbo
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis mmvetgpt4turbo 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.
- 01ACQwen2-VL-72B-InstructAlibaba Cloud / Qwen Team
- Score
- 74.0%
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures MMVetGPT4Turbo, not total model capability
Selection summary
Best AI Models for MMVetGPT4Turbo
Qwen2-VL-72B-Instruct currently leads MMVetGPT4Turbo with 74.0%. 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 MMVetGPT4Turbo?
What MMVetGPT4Turbo measures and how its scores work.
MM-Vet evaluation using GPT-4 Turbo for scoring. This variant of MM-Vet examines large multimodal models on complicated multimodal tasks requiring integrated capabilities across six core vision-language abilities: recognition, knowledge, spatial awareness, language generation, OCR, and math.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MMVetGPT4Turbo
- Modality
- multimodal
- Primary category
- math
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mmvetgpt4turbo|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MMVetGPT4Turbo.
Which model scores highest on MMVetGPT4Turbo?
Qwen2-VL-72B-Instruct is currently ranked first with 74.0%.
What does MMVetGPT4Turbo measure?
MM-Vet evaluation using GPT-4 Turbo for scoring. This variant of MM-Vet examines large multimodal models on complicated multimodal tasks requiring integrated capabilities across six core vision-language abilities: recognition, knowledge, spatial awareness, language generation, OCR, and math.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.