A Chinese open-source AI model is shown to rival top-tier global competitors such as DeepSeek R1, despite its smaller size, representing another step forward in balancing performance and efficiency in AI application.

近日，中國一款新型開源人工智能模型發(fā)布,，盡管規(guī)模較小,，實力卻能比肩DeepSeek-R1等全球頂級競品，標志著人工智能應(yīng)用在平衡性能與效率方面更進一步,。

The QwQ-32B, unveiled last Thursday by Alibaba's Qwen team, operates on just 24 GB of video memory with only 32 billion parameters, while DeepSeek's R1 demands 1,600 GB to run its 671 billion parameters, thus realizing a 98-percent reduction.

阿里巴巴通義千問團隊上周四推出的QwQ-32B模型,，僅需24GB顯存且只要320億參數(shù)即可運行，相比DeepSeek-R1模型運行其6710億參數(shù)需要1600GB顯存,，顯存需求減少了98%,。

Also, compared to OpenAI's o1-mini and Anthropic's Sonnet 3.7, Qwen's AI model has substantially lower computational requirements.

不僅如此，相較于OpenAI的o1-mini模型和Anthropic的Sonnet3.7模型,，QwQ-32B的計算需求也大幅下降,。

Kyle Corbitt, a former Google engineer, published his testing results on social media platform X, showing that "the smaller, open-weight model can match state-of-the-art reasoning performance."

前谷歌工程師凱爾·科爾比特（Kyle Corbitt）在社交媒體平臺X上公布了他的測試結(jié)果，結(jié)果顯示“這款參數(shù)更少的開源模型能夠達到最先進的推理性能水平”,。

According to Corbitt's team, QwQ-32B achieved the second-highest score in a deductive reasoning benchmark via a method called reinforcement learning (RL), outperforming R1, o1 and o3-mini, while nearly matching Sonnet 3.7's performance at an inference cost more than 100-fold lower than that required by Sonnet 3.7.

據(jù)科爾比特團隊透露,，在演繹推理基準測試中，QwQ-32B運用強化學習（RL）方法取得了第二高的分數(shù),，超越了R1,、o1和o3-mini，且推理成本較Sonnet 3.7降低100多倍,，性能卻與之相當,。

"AI isn't just getting smarter, it's learning how to evolve," commented Shashank Yadav, CEO of Fraction AI. "QwQ-32B proves that reinforcement learning can out-compete brute-force scaling."

Fraction AI首席執(zhí)行官沙尚克·亞達夫（Shashank Yadav）對此評論道：“人工智能不僅變得更智能了，它還在學習如何進化,。QwQ-32B證明了,，強化學習可以超越傳統(tǒng)單純依靠擴大規(guī)模的方法?！?/p>

"We found RL training enhances performance, particularly in math and coding tasks. Its expansion can enable medium-sized models to match large MoE models' performance," read Qwen's blog article on Github.

通義千問團隊在GitHub博客中也指出,，強化學習訓(xùn)練對模型在數(shù)學和編程任務(wù)中的表現(xiàn)提升尤為顯著，有望推動中型模型達到大型混合專家（MoE）模型的性能層級,。

Qwen's new model is expected to enhance the feasibility of local operations for generative AI products on computers and even mobile devices in the future.

未來,，該模型有望提高生成式AI產(chǎn)品在電腦乃至移動設(shè)備上進行本地運行的可行性,。

Awni Hannun, a computer scientist at Apple, has run QwQ-32B on the Apple computer powered by its M4 Max chip, and it appears to be "running nicely."

蘋果公司計算機科學家奧尼·漢農(nóng)（Awni Hannun）在搭載M4 Max芯片的蘋果電腦上運行了QwQ-32B，結(jié)果發(fā)現(xiàn)運行非常流暢,。

China's national supercomputing internet platform last Saturday announced the launch of the API interface service for QwQ-32B. In addition, Biren Technology, a Shanghai-based GPU chip designer, announced Sunday that it has launched an all-in-one machine capable of running this model.

中國國家超算互聯(lián)網(wǎng)平臺9日宣布推出QwQ-32B的應(yīng)用程序編程接口（API）服務(wù),。此外，上海的GPU芯片設(shè)計公司壁仞科技周日宣布,，已推出一款能夠運行QwQ-32B模型的一體機,。

QwQ-32B is freely accessible as an open-source model that anyone can run, following DeepSeek's path of facilitating wider application of AI technologies worldwide and contributing China's wisdom to the world.

QwQ-32B作為一款開源模型可供任何人自由使用和運行，它也延續(xù)了DeepSeek推動AI技術(shù)全球普及的路線,，為世界貢獻了中國智慧,。

Alibaba also recently open-sourced its AI video-generating model Wan2.1, which is available for download on Alibaba Cloud's AI model community, Model Scope and the collaborative AI platform Hugging Face.

此外，阿里巴巴最近還開源了其人工智能視頻生成模型通義萬相2.1（Wan2.1）,，該模型可在阿里云的人工智能模型社區(qū)魔搭（Model Scope）以及人工智能協(xié)作平臺Hugging Face上下載,。

The e-commerce and cloud-computing giant has announced a plan to invest more than 380 billion yuan (about $52.97 billion) in building cloud and AI hardware infrastructure over the next three years.

作為電子商務(wù)與云計算領(lǐng)域的領(lǐng)軍企業(yè)，阿里巴巴還宣布了一項重大投資計劃,。未來三年,，阿里巴巴將投入超過 3800 億元人民幣（約合 529.7 億美元），用于構(gòu)建云和人工智能硬件基礎(chǔ)設(shè)施,。