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港股异动 | 七牛智能(02567)涨超5% 七牛云AI推理平台上新GPT-OSS 相关模型可通过控制台或API快速调用
智通财经网· 2025-08-11 02:53
Core Viewpoint - Qiniu Intelligent (02567) has seen a significant increase in stock price, rising over 5% and accumulating a gain of over 50% in the past month, attributed to the release of OpenAI's new open-source language model series, GPT-OSS [1] Company Summary - Qiniu Intelligent's stock price rose by 5.71%, reaching HKD 1.48, with a trading volume of HKD 2.0961 million [1] - The company has quickly deployed and optimized the newly released GPT-OSS models from OpenAI, integrating them into Qiniu Cloud's model marketplace [1] Industry Summary - OpenAI has launched the GPT-OSS series, which includes two models: GPT-OSS-120b and GPT-OSS-20b, marking its first open-source model release since GPT-2 in 2019 [1] - The GPT-OSS models are designed as community general-purpose large language models, featuring key capabilities such as function calling, tool invocation, and structured output, suitable for building agent architectures and knowledge Q&A [1]
七牛智能涨超5% 七牛云AI推理平台上新GPT-OSS 相关模型可通过控制台或API快速调用
Zhi Tong Cai Jing· 2025-08-11 02:53
Group 1 - Qiniu Intelligent (02567) has seen a stock price increase of over 5%, with a cumulative rise of more than 50% over the past month, currently trading at 1.48 HKD with a transaction volume of 2.0961 million HKD [1] - OpenAI has released a new open-source language model series called GPT-OSS, which includes two models: GPT-OSS-120b and GPT-OSS-20b, marking the first open-source model release since GPT-2 in 2019 [1] - The GPT-OSS models are designed as community general-purpose language models, featuring key capabilities such as function calling, tool invocation, and structured output, suitable for building agent architectures, knowledge Q&A, and RAG retrieval generation scenarios [1] Group 2 - Qiniu Cloud has promptly completed the deployment and tuning of the GPT-OSS models, which are now integrated into the Qiniu Cloud model marketplace, allowing developers to quickly access them via console or API without local deployment [1]