multimodal benchmark
VLMsAreBlind
A vision-language benchmark that probes blind spots and brittle reasoning in multimodal models.
Updated Aug 11, 2026
Models4
Model coverage4
MetricScore
EvidenceB
VLMsAreBlind Ranking
Higher score ranks better on this benchmark.
| 01 | AC | 97.0% | 100.0% | 4 | C | |
| 02 | AC | 97.0% | 66.7% | 4 | C | |
| 03 | AC | 96.9% | 33.3% | 4 | C | |
| 04 | AC | 96.7% | 0.0% | 4 | C |
VLMsAreBlind Score Distribution
A closer view of the leading scores on this benchmark.
VLMsAreBlind Highlights
The leading models and scores on this benchmark.
What is VLMsAreBlind?
What VLMsAreBlind measures and how its scores work.
A vision-language benchmark that probes blind spots and brittle reasoning in multimodal models.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- VLMsAreBlind
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- vlmsareblind|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about VLMsAreBlind.
Which model scores highest on VLMsAreBlind?
Qwen3.5-35B-A3B is currently ranked first with 97.0%.
What does VLMsAreBlind measure?
A vision-language benchmark that probes blind spots and brittle reasoning in multimodal models.
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.