百亿亏损换一张门票，国产AI大模型“流血”抢滩上市

Core Insights - The article discusses the simultaneous IPO applications of two leading AI companies, MiniMax and Zhiyu AI, highlighting the competitive landscape and financial challenges within the AI industry [4][6]. Company Overview - MiniMax, founded in early 2022, has raised over $1.5 billion and holds approximately $1.1 billion in cash, while Zhiyu AI, with a different operational focus, submitted its IPO application just 48 hours earlier [4][6]. - MiniMax focuses on multi-modal models and AI-native products, while Zhiyu AI emphasizes a foundational model and open-source ecosystem [7][9]. Financial Performance - MiniMax reported a loss of $269 million in 2023, projected to increase to $465 million in 2024, and has already incurred a loss of $512 million in the first nine months of 2025, totaling $1.32 billion in cumulative losses [11]. - Zhiyu AI's losses are also significant, with a reported loss of 788 million yuan in 2023, escalating to 2.958 billion yuan in 2024, and 2.358 billion yuan in the first half of 2025, leading to over 6.2 billion yuan in cumulative losses [11]. Industry Challenges - The AI industry faces high operational costs, particularly in research and development, with MiniMax's R&D expenses exceeding 2000% of its revenue at one point, and Zhiyu AI having over 70% of its workforce in R&D [13]. - The rising costs of AI deployment and the uneven distribution of benefits between developers and cloud service providers pose significant challenges to the ecosystem [10]. Market Dynamics - The IPOs of MiniMax and Zhiyu AI are expected to provide a benchmark for valuation in the AI sector, which has struggled with unclear profit models and declining investment in the primary market [14]. - The transition from "storytelling" to "proving commercial value" is anticipated to reshape the industry, with a focus on scalable business scenarios rather than just technological advancements [16]. Future Outlook - The AI industry is at a crossroads, needing to balance cost reduction and efficiency improvements while seeking sustainable commercialization paths [18]. - The upcoming year is seen as pivotal for AI applications, with potential market consolidation and a shift towards efficiency as a competitive advantage [19].