UI-Venus-1.5 技術報告

UI-Venus-1.5 Technical Report

February 9, 2026

作者: Veuns-Team, Changlong Gao, Zhangxuan Gu, Yulin Liu, Xinyu Qiu, Shuheng Shen, Yue Wen, Tianyu Xia, Zhenyu Xu, Zhengwen Zeng, Beitong Zhou, Xingran Zhou, Weizhi Chen, Sunhao Dai, Jingya Dou, Yichen Gong, Yuan Guo, Zhenlin Guo, Feng Li, Qian Li, Jinzhen Lin, Yuqi Zhou, Linchao Zhu, Liang Chen, Zhenyu Guo, Changhua Meng, Weiqiang Wang

cs.AI

摘要

圖形使用者介面代理已成為自動化數位環境互動的強大範式，然而要同時實現廣泛通用性與穩定高效的任務執行能力仍具挑戰性。本報告提出UI-Venus-1.5——專為強健現實應用設計的統一端到端GUI代理。該模型系列包含兩個稠密版本（2B與8B）及一個專家混合版本（30B-A3B），以滿足各類下游應用場景需求。相較前代版本，UI-Venus-1.5引入三大關鍵技術突破：（1）透過整合30餘個數據集、百億標記量的綜合中期訓練階段，建立基礎GUI語義理解；（2）採用全軌跡推演的線上強化學習，使訓練目標與大規模環境中的長時程動態導航需求對齊；（3）透過模型融合技術構建統一GUI代理，將領域專精模型（基礎定位、網頁端與移動端）整合為協同運作的單一檢查點。大量實驗表明，UI-Venus-1.5在ScreenSpot-Pro（69.6%）、VenusBench-GD（75.0%）和AndroidWorld（77.6%）等基準測試中創下最新性能紀錄，顯著超越先前強基線模型。此外，該模型在多元中文移動應用場景中展現出穩健的導航能力，可於真實環境中有效執行使用者指令。程式碼：https://github.com/inclusionAI/UI-Venus；模型：https://huggingface.co/collections/inclusionAI/ui-venus

English

GUI agents have emerged as a powerful paradigm for automating interactions in digital environments, yet achieving both broad generality and consistently strong task performance remains challenging.In this report, we present UI-Venus-1.5, a unified, end-to-end GUI Agent designed for robust real-world applications.The proposed model family comprises two dense variants (2B and 8B) and one mixture-of-experts variant (30B-A3B) to meet various downstream application scenarios.Compared to our previous version, UI-Venus-1.5 introduces three key technical advances: (1) a comprehensive Mid-Training stage leveraging 10 billion tokens across 30+ datasets to establish foundational GUI semantics; (2) Online Reinforcement Learning with full-trajectory rollouts, aligning training objectives with long-horizon, dynamic navigation in large-scale environments; and (3) a single unified GUI Agent constructed via Model Merging, which synthesizes domain-specific models (grounding, web, and mobile) into one cohesive checkpoint. Extensive evaluations demonstrate that UI-Venus-1.5 establishes new state-of-the-art performance on benchmarks such as ScreenSpot-Pro (69.6%), VenusBench-GD (75.0%), and AndroidWorld (77.6%), significantly outperforming previous strong baselines. In addition, UI-Venus-1.5 demonstrates robust navigation capabilities across a variety of Chinese mobile apps, effectively executing user instructions in real-world scenarios. Code: https://github.com/inclusionAI/UI-Venus; Model: https://huggingface.co/collections/inclusionAI/ui-venus