Open CaptchaWorld: A Comprehensive Web-based Platform for Testing and
  Benchmarking Multimodal LLM Agents
Authors: name: Yaxin Luo, name: Zhaoyi Li, name: Jiacheng Liu, name: Jiacheng Cui, name: Xiaohan Zhao, name: Zhiqiang Shen

CAPTCHAs have been a critical bottleneck for deploying web agents in
real-world applications, often blocking them from completing end-to-end
automation tasks. While modern multimodal LLM agents have demonstrated
impressive performance in static perception tasks, their ability to handle
interactive, multi-step reasoning challenges like CAPTCHAs is largely untested.
To address this gap, we introduce Open CaptchaWorld, the first web-based
benchmark and platform specifically designed to evaluate the visual reasoning
and interaction capabilities of MLLM-powered agents through diverse and dynamic
CAPTCHA puzzles. Our benchmark spans 20 modern CAPTCHA types, totaling 225
CAPTCHAs, annotated with a new metric we propose: CAPTCHA Reasoning Depth,
which quantifies the number of cognitive and motor steps required to solve each
puzzle. Experimental results show that humans consistently achieve near-perfect
scores, state-of-the-art MLLM agents struggle significantly, with success rates
at most 40.0% by Browser-Use Openai-o3, far below human-level performance,
93.3%. This highlights Open CaptchaWorld as a vital benchmark for diagnosing
the limits of current multimodal agents and guiding the development of more
robust multimodal reasoning systems. Code and Data are available at this https
URL.