multimodal benchmark
OmniBench
A novel multimodal benchmark designed to evaluate large language models' ability to recognize, interpret, and reason across visual, acoustic, and textual inputs simultaneously. Comprises 1,142 question-answer pairs covering 8 task categories from basic perception to complex inference, with a unique constraint that accurate responses require integrated understanding of all three modalities.
Updated Aug 11, 2026
Models1
Model coverage1
MetricScore
EvidenceB
OmniBench Ranking
Higher score ranks better on this benchmark.
| 01 | AC | 56.1% | 100.0% | 1 | C |
OmniBench Highlights
The leading models and scores on this benchmark.
What is OmniBench?
What OmniBench measures and how its scores work.
A novel multimodal benchmark designed to evaluate large language models' ability to recognize, interpret, and reason across visual, acoustic, and textual inputs simultaneously. Comprises 1,142 question-answer pairs covering 8 task categories from basic perception to complex inference, with a unique constraint that accurate responses require integrated understanding of all three modalities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- OmniBench
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- omnibench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about OmniBench.
Which model scores highest on OmniBench?
Qwen2.5-Omni-7B is currently ranked first with 56.1%.
What does OmniBench measure?
A novel multimodal benchmark designed to evaluate large language models' ability to recognize, interpret, and reason across visual, acoustic, and textual inputs simultaneously. Comprises 1,142 question-answer pairs covering 8 task categories from basic perception to complex inference, with a unique constraint that accurate responses require integrated understanding of all three modalities.
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.