multimodal benchmark
VLMsAreBiased Leaderboard
VLMsAreBiased is a multimodal benchmark that evaluates whether vision-language models rely on visual evidence or language priors when answering.
Updated Sep 5, 2026
Models2
Model coverage2
MetricScore
EvidenceB
VLMsAreBiased Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelBY | Score83.60% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelBY | Score68.30% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
VLMsAreBiased Highlights
The leading models and scores on this benchmark.
VLMsAreBiased Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for VLMsAreBiased
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is VLMsAreBiased?
What VLMsAreBiased measures and how its scores work.
VLMsAreBiased is a multimodal benchmark for evaluating vision-language models.
It measures whether vision-language models rely on visual evidence or fall back on language priors when answering.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- VLMsAreBiased
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about VLMsAreBiased.
Which model scores highest on VLMsAreBiased?
Seed 2.1 Pro is currently ranked first with 83.60%.
What are the top three models on VLMsAreBiased?
The current leaders are Seed 2.1 Pro (83.60%) and Seed 2.1 Turbo (68.30%).
Which VLMsAreBiased model has the lowest official input price?
No matched official input price is currently available.
Which models are fastest among VLMsAreBiased results?
No matched runtime record is currently available.
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.