观察 | 智谱AI的钱到底花哪儿了？

Core Viewpoint - The essence of investment is to bet on future value, and the analysis of the company's losses should consider whether the funds have been transformed into valuable resources rather than simply being "burned" [1][4]. Group 1: Financial Analysis - In the first half of 2025, the company's R&D expenses amounted to 1.59 billion RMB, with 1.145 billion RMB (71.8%) allocated to cloud services and hardware purchases, a significant increase from 17.3% in 2022 [8][9]. - The company has accumulated R&D investments of approximately 4 billion RMB (around 600 million USD) over the years, producing competitive models that align with international standards [20]. - The company has achieved a gross profit margin of around 50%, indicating potential for profitability as revenue scales up [42]. Group 2: Resource Allocation and Strategy - The company is systematically converting funds into computing power resources, which are essential for AI model training [10][11]. - The strategy includes a dual approach: expanding API services for developers while also providing localized deployment services for enterprise clients, balancing scale and profitability [35]. - The company has adapted its models to over 40 domestic chip types, indicating a proactive strategy in diversifying computing resources [24][26]. Group 3: Industry Context and Competitive Landscape - The industry is currently in a "arms race" phase, where significant upfront investments are necessary to secure a competitive position [45]. - Different technical routes correspond to different business scenarios; the company focuses on stability and comprehensive support for localized deployments, which require substantial initial investment [32][34]. - The competitive landscape is evolving, with other companies demonstrating lower-cost model training, which pressures the industry to optimize resource utilization [30][31]. Group 4: Future Outlook - Predictions indicate that the cost of computing power will decline, driven by rapid iterations of domestic AI chips and ongoing algorithm optimizations [37][39]. - The company is expected to see a gradual reduction in R&D expense ratios over the next two to three years, enhancing investment efficiency [42]. - Investors are looking at the long-term potential, betting on the company's ability to become a leading player in the AI model sector within three to five years [48].