Core Viewpoint - The rise of non-GPU chip forces is unstoppable, indicating a significant shift in the global computing power industry, traditionally dominated by NVIDIA GPUs [1][6]. Group 1: Recent Developments in the Computing Power Industry - Shanghai's leading GPU company, Muxi Co., recently listed on the STAR Market, with its stock price surging by 687.79% to a market cap of 329.88 billion yuan [1]. - Google’s TPU has secured orders worth over 100 billion yuan, breaking the GPU monopoly in the computing power market, while Broadcom's CEO revealed a total order of 21 billion USD (approximately 148.6 billion yuan) from Anthropic [2]. - In China, the computing power industry is also heating up, with AI chip company Qingwei Intelligence securing over 2 billion yuan in financing, supported by a rare investment lineup [2]. Group 2: Market Trends and Dynamics - The global computing power market is experiencing a transformation, with the long-standing NVIDIA GPU monopoly beginning to loosen [2][6]. - The demand for general computing power has led to NVIDIA GPUs dominating the market, but alternatives like Google’s TPU and Amazon’s Trainium3 are starting to replace GPUs in specific scenarios [2][8]. - By the first half of 2025, non-GPU computing cards are expected to account for 30% of the domestic market [2]. Group 3: Investment Movements - Intel is reportedly planning to acquire AI chip unicorn SambaNova for 1.6 billion USD (approximately 11.29 billion yuan) to regain competitiveness in the AI era [3]. - Non-GPU unicorn Groq has raised over 3 billion USD (approximately 21.3 billion yuan) in funding over the past two years [3]. Group 4: Industry Structure and Future Directions - The computing power industry is expected to face path differentiation, driven by demand, technology, and ecosystem development [8][10]. - The need for efficient computing solutions is pushing companies to seek alternatives to the traditional GPU-centric model, especially as AI applications diversify across various industries [8][9]. - The traditional von Neumann architecture is facing challenges, necessitating architectural innovations to overcome performance limitations [9]. Group 5: Non-GPU Market Growth - Gartner predicts that by 2027, the demand for AI inference applications will lead to AI accelerators (typically non-GPU AI-specific chips) surpassing GPU shipments [16]. - In the first half of this year, China's non-GPU chip market has shown significant growth, with projections indicating a market share of nearly 50% by 2028 [16]. Group 6: Domestic Chip Companies and Their Strategies - Key players in the domestic non-GPU sector include Kunlun Chip, Cambricon, and Qingwei Intelligence, each representing different technological routes [25][29]. - Cambricon and Kunlun Chip focus on ASIC routes, while Qingwei Intelligence emphasizes reconfigurable computing architectures [29][30]. - The ASIC architecture, exemplified by Google’s TPU, offers high performance and efficiency, but requires significant time and resources for customization [30][31]. Group 7: Reconfigurable Computing Advantages - Reconfigurable computing is gaining momentum, addressing the inefficiencies of GPUs and the rigidity of ASICs, thus balancing performance and cost [32][37]. - Qingwei Intelligence's reconfigurable chips have achieved over 30 million units shipped, with significant orders expected in the coming years [32]. - The technology supports efficient inter-chip communication, avoiding bandwidth bottlenecks and communication delays inherent in traditional architectures [33]. Group 8: Conclusion - The AI computing power landscape is evolving towards a diversified and heterogeneous integration, with GPUs maintaining dominance in general-purpose applications while non-GPU routes rapidly rise in AI inference and specialized computing needs [39][41].

Core Insights - Qingwei Intelligent, a leading AI chip company in Beijing, announced the completion of over 2 billion RMB in Series C financing and initiated preparations for an IPO, aiming to become the first listed benchmark in the domestic "non-GPU" new architecture chip sector [1][4] Financing and Investment - The financing round was led by Beijing state-owned enterprise Jingneng Group, with participation from multiple institutions including Beichuang Investment, Jiantou Investment, Wuyuefeng Science and Technology Innovation, and Chengdu Science and Technology Investment, among others [3] - The funds will focus on three main areas: R&D of next-generation reconfigurable chip core technologies, large-scale implementation of intelligent computing scenarios, and the cultivation of high-end technical talent [3] Technology and Product Development - Qingwei Intelligent has developed a unique non-GPU technology path, leveraging 20 years of technical accumulation from Tsinghua University [3] - The TX81 reconfigurable AI chip achieves high bandwidth and low latency data flow through "C2C computing grid technology," with a single server's computing power reaching 4 PFLOPS, supporting trillion-parameter large model deployment, reducing costs by 50%, and improving energy efficiency by three times compared to traditional solutions [3] - The company has adapted its products to mainstream large models and has received over 20,000 orders for reconfigurable computing cards, ranking sixth in domestic AI acceleration card shipments in the first half of 2025 [3] Leadership and Market Position - The founder and CEO, Wang Bo, was recently awarded the title of "Annual Entrepreneur of the IC Design Industry in China 2025," recognized for his strategic vision in promoting the localization of new architecture AI chips [4] - The simultaneous advancement of financing and IPO preparations is seen as a dual validation of the company's technological accumulation and commercial achievements [4] Industry Impact - The IPO preparations are expected to empower the company with capital and set an industry benchmark for the non-GPU sector, promoting the ecological development of reconfigurable computing technology [4] - With steady progress in funding and the IPO process, the company is poised to further break through core technologies for the next generation of chips and deepen the implementation of intelligent computing scenarios, providing robust and controllable computing power for the digital economy [4]