ChartQA

ChartQA is a large-scale benchmark comprising 9.6K human-written questions and 23.1K questions generated from human-written chart summaries, designed to evaluate models' abilities in visual and logical reasoning over charts.

Claude 3.5 Sonnet from Anthropic currently leads the ChartQA leaderboard with a score of 0.908 across 24 evaluated AI models.

Paper

AnthropicClaude 3.5 Sonnet leads with 90.8%, followed by MetaLlama 4 Maverick at 90.0% and Alibaba Cloud / Qwen TeamQwen2.5 VL 72B Instruct at 89.5%.

Progress Over Time

Interactive timeline showing model performance evolution on ChartQA

State-of-the-art frontier
Open
Proprietary

ChartQA Leaderboard

24 models
ContextCostLicense
1
2400B
3
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
72B
4
Amazon
Amazon
5109B
6
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
73B
7
Mistral AI
Mistral AI
124B
824B
9
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
8B
10
Amazon
Amazon
11
DeepSeek
DeepSeek
27B
12
OpenAI
OpenAI
128K$2.50 / $10.00
1390B
14
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
7B
1516B
1611B
174B
17
Mistral AI
Mistral AI
12B
196B
203B
2127B
22
2312B
244B
Notice missing or incorrect data?

FAQ

Common questions about ChartQA.

What is the ChartQA benchmark?

ChartQA is a large-scale benchmark comprising 9.6K human-written questions and 23.1K questions generated from human-written chart summaries, designed to evaluate models' abilities in visual and logical reasoning over charts.

What is the ChartQA leaderboard?

The ChartQA leaderboard ranks 24 AI models based on their performance on this benchmark. Currently, Claude 3.5 Sonnet by Anthropic leads with a score of 0.908. The average score across all models is 0.842.

What is the highest ChartQA score?

The highest ChartQA score is 0.908, achieved by Claude 3.5 Sonnet from Anthropic.

How many models are evaluated on ChartQA?

24 models have been evaluated on the ChartQA benchmark, with 0 verified results and 24 self-reported results.

Where can I find the ChartQA paper?

The ChartQA paper is available at https://arxiv.org/abs/2203.10244. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does ChartQA cover?

ChartQA is categorized under multimodal, reasoning, and vision. The benchmark evaluates multimodal models.

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