prithivMLmods/Herculis-CUA-GUI-Actioner-4B

VISIONPricing:Input $0.32 / Cached $0.016 / Output $1.6Concurrent Unit Cost:1Model Size:3BQuant:BF16Context Size:32kPublished:Dec 12, 2025License:otherArchitecture:Transformer0.0K Featherless Exclusive Cold

Herculis-CUA-GUI-Actioner-4B by prithivMLmods is a 3 billion parameter multimodal Computer Use Agent (CUA) designed for GUI understanding, UI localization, and action execution across web, desktop, and mobile environments. With a 32768 token context length, it focuses on visual grounding, intent-driven actioning, and UI-based question answering (VQA). This model excels at translating natural language instructions into structured UI actions and automating multi-step tasks like form filling and navigation, making it suitable for natural language driven computer control and RPA-style automation.

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Herculis-CUA-GUI-Actioner-4B Overview

Herculis-CUA-GUI-Actioner-4B is a 3 billion parameter multimodal Computer Use Agent (CUA) developed by prithivMLmods. This model is specifically engineered for comprehensive GUI understanding, UI localization, and the execution of actions across diverse platforms including web, desktop, and mobile interfaces. It integrates visual grounding, intent-driven actioning, and UI-based Visual Question Answering (VQA) to enable reliable interaction with real-world software.

Key Capabilities

  • GUI Localization and Visual Grounding: Accurately identifies UI elements (buttons, text fields, menus, icons, dialogs) across varied layouts and resolutions.
  • Action Planning and Execution: Converts natural language instructions into structured UI actions such as click, type, scroll, drag, select, and navigate, incorporating step-wise reasoning.
  • UI-Based Question Answering (VQA): Provides answers to questions grounded in the current screen state, including element states, content verification, and workflow guidance.
  • Cross-Platform Computer Use: Maintains consistent behavior and robust visual understanding across web applications, desktop software, and mobile interfaces.
  • Multi-Step Task Automation: Manages long-horizon tasks like form filling, settings configuration, dashboard navigation, and tool-driven workflows.
  • Context-Aware Interaction: Sustains task context across screen changes for reliable end-to-end task completion.

Good For

  • Natural language driven computer and GUI control.
  • Automated form filling and workflow execution.
  • UI-based question answering and verification.
  • Web, desktop, and mobile agent systems.
  • RPA-style automation with visual grounding.
  • Assistive agents for accessibility and productivity.

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2 models