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SenseTime Unveils SenseNova 6.7 Flash-Lite With Enhanced Multimodal Capabilities

SenseTime Unveils SenseNova 6.7 Flash-Lite With Enhanced Multimodal Capabilities

July 28, 2026
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The AI landscape is shifting from a focus on massive parameters to lightweight, high-efficiency solutions. SenseTime today unveiled its new lightweight multimodal intelligent agent model—SenseNova 6.7 Flash-Lite. Designed for real-world workflows, this model leverages an innovative native multimodal architecture to overcome the limitations of traditional agents in handling complex, long-chain tasks.

Diagram of SenseTime's lightweight multimodal model

The model's core strength is its superior visual understanding and logical decision-making. Unlike earlier approaches that required an intermediate visual-to-text conversion, SenseNova 6.7 Flash-Lite directly interprets complex web layouts, document structures, and financial charts. This integrated see-think-act mechanism delivers high success rates in demanding office tasks like data analysis, in-depth research, and automated slide generation.

For real-world enterprise deployment, efficiency and cost are critical. According to official data, by removing the intermediate conversion step, the model retains a small parameter footprint while delivering top-tier agent capabilities. In high-frequency scenarios like information retrieval, it consumes roughly 60% fewer tokens than text-only agents and provides millisecond-level response times.

Graphic illustrating SenseNova 6.7 Flash-Lite capabilities

To further reduce the entry barrier for developers and foster ecosystem growth, SenseTime has introduced a limited-time free offer called the SenseNova Token Plan. Developers who join receive an unrestricted usage quota of 1,500 calls, refreshed every five hours during the first month. Additionally, SenseTime has packaged the model's core office skills into SenseNova-Skills, now open-sourced on GitHub. This initiative aims to help developers more easily build high-performance agent applications through shared technology.

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