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中科大开源智能体驱动长上下文训练范式：30B模型媲美Qwen3-235B

USTC Open-Sources Agent-Driven Long-Context Training Paradigm: 30B Matches Qwen3-235B

Primary sourcepandaily@[email protected] (Pandaily)
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Why we picked it

中科大用30B模型打平235B的长上下文能力，做长上下文训练的团队可以直接复用这套开源范式，省下大量算力和数据成本。

中国科学技术大学（USTC）研究人员开源了一种创新的智能体驱动长上下文训练范式，该范式通过智能体引导的数据生成和训练策略，显著提升了长上下文处理效率。

Body

实验表明，一个30亿参数的模型在长上下文任务上达到了与阿里巴巴Qwen3-235B模型相当的性能，而参数量仅为后者的八分之一。这一突破降低了长上下文模型训练的门槛，为资源有限的团队提供了高效方案。

该范式已开源，有望推动长上下文AI应用的普及。

Original · pandaily

USTC Open-Sources Agent-Driven Long-Context Training Paradigm: 30B Matches Qwen3-235B

Researchers at the University of Science and Technology of China (USTC) have open-sourced a novel agent-driven long-context training paradigm that achieves breakthrough efficiency — a 30-billion-parameter model matching the performance of Alibaba'...

Industry Coordinates & Source Verification

This report is categorized under AITOP's "Papers" desk, focusing on China's AI industry and domestic foundation model ecosystem. Within our cross-regional analytical framework, it directly maps to US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include 长上下文, 智能体, 开源/仓库, 训练范式.

Primary source verification: published directly by pandaily with first-party authority.

#长上下文#智能体#开源/仓库#训练范式#USTC

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