清程极智推出AI Ping平台 瞄准模型API服务需求

Core Insights - The core task of AI infrastructure is shifting from training and inference of large models to a new phase focused on "intelligent circulation," emphasizing the efficient and stable use of model capabilities in real business scenarios [1] - The market demand for model API services is emerging as the industry transitions to a stage where the focus is on how to operate models long-term, stably, and at scale [1] Company Overview - Qingcheng Jizhi was founded in December 2023 in Beijing, with a core founding team from Tsinghua University's Computer Science Department [1] - The company has previously launched the "Bagua Furnace" training system and the "Chitu" inference engine to support efficient training and deployment of models across various computing powers [1] Product Development - The AI Ping platform, launched by Qingcheng Jizhi, offers a one-stop AI evaluation and API service routing platform, aimed at enhancing the infrastructure capabilities during the application phase of large models [1] - AI Ping covers a complete chain from "evaluation—access—routing—optimization," focusing on real business scenarios and providing long-term observation of key metrics such as latency, stability, throughput, and cost-effectiveness for different model APIs [2] Market Analysis - A joint report with Huqing Puzhi titled "Large Model API Service Industry Analysis Report (2025)" indicates that DeepSeek and Qwen series models dominate the open-source model API calls, with significant performance differences among service providers [3] - The report highlights that the average daily consumption of large models in China's enterprise market reached 10.2 trillion tokens in the first half of last year, indicating a shift from seeking a single strongest model to finding optimal solutions for specific business scenarios [3]