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multimodal benchmark

CharXiv-D

CharXiv-D is the descriptive questions subset of the CharXiv benchmark, designed to assess multimodal large language models' ability to extract basic information from scientific charts. It contains descriptive questions covering information extraction, enumeration, pattern recognition, and counting across 2,323 diverse charts from arXiv papers, all curated and verified by human experts.

Updated Aug 11, 2026

Models16
Model coverage16
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

CharXiv-D Ranking

Higher score ranks better on this benchmark.

16 rows
Columns

Show columns

01BYSeed 2.1 ProByteDance95.5%100.0%16CAug 11, 2026
02BYSeed 2.1 TurboByteDance94.6%93.3%16CAug 11, 2026
03ACQwen3 VL 32B InstructAlibaba Cloud / Qwen Team90.5%86.7%16CAug 11, 2026
04ACQwen3 VL 32B ThinkingAlibaba Cloud / Qwen Team90.2%80.0%16CAug 11, 2026
05OPGPT-4.5OpenAI90.0%73.3%16CAug 11, 2026
06OPGPT-4.1 miniOpenAI88.4%66.7%16CAug 11, 2026
07COCommand A+Cohere88.0%60.0%16CAug 11, 2026
08OPGPT-4.1OpenAI87.9%53.3%16CAug 11, 2026
09ACQwen3 VL 30B A3B ThinkingAlibaba Cloud / Qwen Team86.9%46.7%16CAug 11, 2026
10ACQwen3 VL 8B ThinkingAlibaba Cloud / Qwen Team85.9%40.0%16CAug 11, 2026
11ACQwen3 VL 30B A3B InstructAlibaba Cloud / Qwen Team85.5%33.3%16CAug 11, 2026
12OPGPT-4oOpenAI85.3%26.7%16CAug 11, 2026
13ACQwen3 VL 4B ThinkingAlibaba Cloud / Qwen Team83.9%20.0%16CAug 11, 2026
14ACQwen3 VL 8B InstructAlibaba Cloud / Qwen Team83.0%13.3%16CAug 11, 2026
15ACQwen3 VL 4B InstructAlibaba Cloud / Qwen Team76.2%6.7%16CAug 11, 2026
16OPGPT-4.1 nanoOpenAI73.9%0.0%16CAug 11, 2026

CharXiv-D Score Distribution

A closer view of the leading scores on this benchmark.

CharXiv-D

CharXiv-D Highlights

The leading models and scores on this benchmark.

Rank #1Seed 2.1 Pro95.5%Rank #2Seed 2.1 Turbo94.6%Rank #3Qwen3 VL 32B Instruct90.5%Rank #4Qwen3 VL 32B Thinking90.2%

What is CharXiv-D?

What CharXiv-D measures and how its scores work.

CharXiv-D is the descriptive questions subset of the CharXiv benchmark, designed to assess multimodal large language models' ability to extract basic information from scientific charts. It contains descriptive questions covering information extraction, enumeration, pattern recognition, and counting across 2,323 diverse charts from arXiv papers, all curated and verified by human experts.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
CharXiv-D
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
charxiv-d|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about CharXiv-D.

Which model scores highest on CharXiv-D?

Seed 2.1 Pro is currently ranked first with 95.5%.

What does CharXiv-D measure?

CharXiv-D is the descriptive questions subset of the CharXiv benchmark, designed to assess multimodal large language models' ability to extract basic information from scientific charts. It contains descriptive questions covering information extraction, enumeration, pattern recognition, and counting across 2,323 diverse charts from arXiv papers, all curated and verified by human experts.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

16 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.