multimodal benchmark
CharXiv-R
CharXiv-R is the reasoning component of the CharXiv benchmark, focusing on complex reasoning questions that require synthesizing information across visual chart elements. It evaluates multimodal large language models on their ability to understand and reason about scientific charts from arXiv papers through various reasoning tasks.
Updated Aug 11, 2026
Models48
Model coverage48
MetricScore
EvidenceB
CharXiv-R Ranking
Higher score ranks better on this benchmark.
CharXiv-R Score Distribution
A closer view of the leading scores on this benchmark.
CharXiv-R Highlights
The leading models and scores on this benchmark.
What is CharXiv-R?
What CharXiv-R measures and how its scores work.
CharXiv-R is the reasoning component of the CharXiv benchmark, focusing on complex reasoning questions that require synthesizing information across visual chart elements. It evaluates multimodal large language models on their ability to understand and reason about scientific charts from arXiv papers through various reasoning tasks.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- CharXiv-R
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- charxiv-r|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about CharXiv-R.
Which model scores highest on CharXiv-R?
Claude Mythos Preview is currently ranked first with 93.2%.
What does CharXiv-R measure?
CharXiv-R is the reasoning component of the CharXiv benchmark, focusing on complex reasoning questions that require synthesizing information across visual chart elements. It evaluates multimodal large language models on their ability to understand and reason about scientific charts from arXiv papers through various reasoning tasks.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
48 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.