README.md

---
dataset_info:
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  - name: id
    dtype: string
  - name: turncase
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  - name: prompt_category
    dtype: string
  - name: eval_focus
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  - name: prompt
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  - name: images_by_turn
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  - name: rubrics
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  splits:
  - name: train
    num_bytes: 3506927656
    num_examples: 1191
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  dataset_size: 3506927656
  configs:
  - config_name: default
    data_files:
    - split: all
      path: data/*.parquet
---

VisuAlToolBench is a challenging benchmark to assess tool-enabled visual perception, transformation, and reasoning in multimodal LLMs. It evaluates whether models can not only think about images but also think with images by actively manipulating visuals (e.g., crop, edit, enhance) and integrating general-purpose tools to solve complex tasks. The dataset contains single-turn and multi-turn tasks across diverse domains, each accompanied by detailed rubrics for systematic evaluation.

Paper: [BEYOND SEEING: Evaluating Multimodal LLMs on Tool-enabled Image Perception, Transformation, and Reasoning](https://static.scale.com/uploads/654197dc94d34f66c0f5184e/vtb_paper.pdf)