ReCAP-32B

ReCAP-32B is a vision-language model fine-tuned from
Qwen/Qwen3-VL-32B-Thinking, designed to enable robust CAPTCHA solving within native GUI agents while preserving general GUI interaction capabilities.

This model is introduced in “CAPTCHA Solving for Native GUI Agents: Automated Reasoning-Action Data Generation and Self-Corrective Training”.

---

🚀 Overview

ReCAP-32B extends a general-purpose GUI agent with CAPTCHA-solving ability by learning from structured reasoning-action trajectories.

It operates end-to-end:

• Input: raw screenshots
• Output: reasoning + executable GUI actions (click, type, drag)

---

✨ Key Features

• Unified agent: Handles both CAPTCHA and general GUI tasks
• Reasoning-action modeling: Learns both decisions and execution
• Self-correction: Improves robustness by learning from failures
• Efficient interaction: Generates multiple actions per step

---

🧠 Capabilities

Supports diverse CAPTCHA types:

• Text / OCR
• Icon selection & matching
• Image grid reasoning
• Slider / drag tasks
• Multi-step interaction challenges

Core skills:

• Visual understanding
• Spatial reasoning
• Continuous control
• Multi-step planning

---

📊 Performance

• ~81.0% success rate on synthetic CAPTCHA benchmark
• Strong improvements on interaction-heavy tasks (e.g., slider, image grid)
• Maintains strong performance on general GUI benchmarks

---

🔒 Ethical Considerations

This model is released for research purposes only.
It is intended to study and improve the robustness of human-verification systems, not to bypass them.