Do Multimodal Agents Really Benefit from Tool Use? A Systematic Study of Capability Gains
Tool-augmented multimodal agents show strong benchmark gains, often taken as evidence that agents have learned to use tools. We argue that this interpretation can be premature: a tool-call trace alone does not show whether the tool supplied answer-critical information. We study two representative ``thinking with images'' agents, Thyme and DeepEyesV2, across real-world understanding, OCR, chart understanding, and mathematical reasoning. Each agent is compared with its Tool-Free counterpart and with a Pure-Text Reasoner trained from the same source pool without tool-calling trajectories. Tool access yields little consistent aggregate improvement, does not reliably reduce generated-token cos...
| Authors | Jiawei Guo, Donglei Yu, Yu Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 June 2026 |
| Last updated at source | 27 August 2026 |
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