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## Ling-2.6-flash: Faster Responses, Stronger Execution, Higher Token Efficiency
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### Introduction
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Today, we announce the official open-source release of **Ling-2.6-flash**, an **instruct model** with **104B total parameters** and **7.4B active parameters**.
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<p align="center">
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<img src="https://mdn.alipayobjects.com/huamei_qa8qxu/afts/img/A*4QxcQrBlTiAAAAAAQXAAAAgAemJ7AQ/original" width="100"/>
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</p>
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<p align="center">🤗 <a href="https://huggingface.co/inclusionAI">Hugging Face</a> | 🤖 <a href="https://modelscope.cn/organization/inclusionAI">ModelScope </a> | 🐙 <a href="https://ling.tbox.cn/chat">ling.tbox.cn</a> | <a href="https://arxiv.org/abs/2606.15079">Tech Report </a></p>
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## Ling-2.6-flash: Faster Responses, Stronger Execution, Higher Token Efficiency
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### Introduction
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Today, we announce the official open-source release of **Ling-2.6-flash**, an **instruct model** with **104B total parameters** and **7.4B active parameters**.
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