Skywork R1V4-Lite - Kunlun Wanwei's lightweight multimodal agent

What is Skywork R1V4-Lite

Skywork R1V4-Lite is a lightweight multimodal agent launched by Kunlun Wanwei. Skywork R1V4-Lite integrates three major capabilities: visual operation, deep reasoning, and task planning. It can complete complex tasks through active image operations (such as cropping, zooming in, and rotating) and web search enhancement. The model requires no user-designed prompts; with just one image, it can automatically observe, reason, and provide answers, making it suitable for scenarios such as real-time question answering, visual retrieval, and intelligent assistants. Skywork R1V4-Lite responds quickly and costs little, demonstrating the strong potential of small models and offering a new path for multimodal agents to move toward open-ended interaction. Skywork R1V4-Liteis already on theSkywork API platformand will soon arrive at OpenRouter。

Main features of Skywork R1V4-Lite

• Active visual operation: Supports operations such as cropping, zooming in, and rotating images, enabling better understanding of image content and solving problems caused by limited viewpoints or insufficient information.
• Deep reasoning and verification: Performs verification of complex tasks through multiple rounds of reasoning and auxiliary tools (such as auxiliary lines), ensuring the rigor and interpretability of results.
• Multimodal deep research: Supports web search and deeply integrates search results with visual reasoning to form a closed loop of "search-reason-verify," expanding the boundaries of reasoning.
• Task planning and execution: Starting from visual input, automatically constructs a task chain, including task decomposition, tool selection, parameter generation, and execution order planning, realizing the shift from "looking at an image and answering" to "looking at an image and acting."
• Real-time interaction and application: Suitable for scenarios such as real-time question answering, visual retrieval, and intelligent assistants, with the characteristics of low latency, high throughput, and low cost.

Technical principles of Skywork R1V4-Lite

• Interleaved training of image operations and deep reasoning: Through the combination of active image operations (such as cropping, zooming in, and rotating) and deep reasoning, the model improves its understanding of complex scenes, enabling it to better handle complex problems such as viewpoint changes and blurred text.
• Multimodal fusion: Deeply integrates visual information with multimodal data such as external search results and text information, achieving cross-modal knowledge expansion and reasoning enhancement by building reasoning scaffolds.
• Task planning and execution chain construction: Starting from visual input, the model can automatically decompose tasks, select tools, generate parameters, and plan execution order, extending the reasoning chain into an executable action chain and realizing proactive task planning.
• Efficient lightweight architecture design: By optimizing the model structure and inheriting advanced lightweight architectures (such as Qwen3 A3B), it achieves high performance with an extremely small parameter scale and features fast response and high throughput.

Project address of Skywork R1V4-Lite

• GitHub repository：https://github.com/SkyworkAI/Skywork-R1V
• arXiv technical paper：https://github.com/SkyworkAI/Skywork-R1V/blob/main/Skywork_R1V4.pdf

Application scenarios of Skywork R1V4-Lite

• Intelligent education: Through image recognition of math problems or foreign language vocabulary, it automatically provides solution steps, vocabulary explanations, and example sentences to assist students in learning.
• E-commerce and retail: Users upload product images, and the model identifies and recommends the same item, compares prices, or generates detailed information, optimizing the shopping experience.
• Travel and transportation: Users photograph landmarks or attractions; the model identifies them and provides location and background information, or generates a travel plan based on the destination, helping with travel.
• Healthcare: The model assists doctors in identifying abnormalities in medical images, or combines image search to provide patients with health advice and disease information, supporting medical decision-making.
• Smart Office: Users photograph files or documents; the model automatically extracts text, translates, or organizes the content, improving office efficiency.