multimodal benchmark
VisualWebBench Leaderboard
A multimodal benchmark designed to assess the capabilities of multimodal large language models (MLLMs) across web page understanding and grounding tasks. Comprises 7 tasks (captioning, webpage QA, heading OCR, element OCR, element grounding, action prediction, and action grounding) with 1.5K human-curated instances from 139 real websites across 87 sub-domains.
Updated Aug 17, 2026
Models2
Model coverage2
MetricScore
EvidenceB
VisualWebBench Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAM Nova ProAmazon | Score79.7% | Percentile100.0% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelAMNova LiteAmazon | Score77.7% | Percentile0.0% | Participants2 | EvidenceC | Evaluated |
VisualWebBench Highlights
The leading models and scores on this benchmark.
VisualWebBench Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for VisualWebBench
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis visualwebbench 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.
- 01AMNova ProAmazon
- Score
- 79.7%
- Price
- $0.80 input / $3.2 output per 1M tokens
- Speed
- Up to 100 tok/s via Bedrock
Strengths
- Ranks #1 of 2 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures VisualWebBench, not total model capability
- 02AMNova LiteAmazon
- Score
- 77.7%
- Price
- $0.06 input / $0.24 output per 1M tokens
- Speed
- Up to 100 tok/s via Bedrock
Strengths
- Ranks #2 of 2 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures VisualWebBench, not total model capability
Selection summary
Best AI Models for VisualWebBench
Nova Pro currently leads VisualWebBench with 79.7%. 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 VisualWebBench?
What VisualWebBench measures and how its scores work.
A multimodal benchmark designed to assess the capabilities of multimodal large language models (MLLMs) across web page understanding and grounding tasks. Comprises 7 tasks (captioning, webpage QA, heading OCR, element OCR, element grounding, action prediction, and action grounding) with 1.5K human-curated instances from 139 real websites across 87 sub-domains.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- VisualWebBench
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- visualwebbench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about VisualWebBench.
Which model scores highest on VisualWebBench?
Nova Pro is currently ranked first with 79.7%.
What does VisualWebBench measure?
A multimodal benchmark designed to assess the capabilities of multimodal large language models (MLLMs) across web page understanding and grounding tasks. Comprises 7 tasks (captioning, webpage QA, heading OCR, element OCR, element grounding, action prediction, and action grounding) with 1.5K human-curated instances from 139 real websites across 87 sub-domains.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
2 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.