UI-TARS 7B

UI-TARS 7B is a multimodal vision-language agent built by ByteDance for graphical user interface work, extending the UI-TARS framework with reinforcement learning. It targets environments that require screen understanding and action, including desktop interfaces, web browsers, mobile systems, and games, making it a fit for GUI automation, agent prototyping, and interface-grounded reasoning tasks. The model accepts image and text input and produces text output, positioning it as a perception-and-decision layer rather than a general chat assistant.

On the practical side, UI-TARS 7B is openly weighted and ships with a wide decoding toolkit covering frequency penalty, logit bias, max tokens, presence penalty, repetition penalty, seed, stop, temperature, top-k, and top-p, which lets developers tune sampling behavior for deterministic agent loops or exploratory control. The 128,000-token context window paired with a 2,048-token completion ceiling suits short, action-oriented outputs such as clicks, typed commands, and structured agent responses rather than long-form generation. For teams building vision-driven agents on a budget, it offers a low entry cost and works well for high-volume, cross-modal GUI workflows where image grounding matters more than extended prose.