Tou Bao Yan Jiu Yuan·2025-07-16 12:01Investment Rating - The report does not explicitly state an investment rating for the China Large Model All-in-One Machine industry Core Insights - The rapid development of artificial intelligence technologies has led to the emergence of large model all-in-one machines, which provide end-to-end support for the development, training, deployment, and operation of large models [2] - The market for large model all-in-one machines in China is characterized by increasing competition among major technology companies, each launching their own products [2] Summary by Sections Market Analysis - The market for large model all-in-one machines is diversifying, with products priced between 500,000 to 5 million yuan, catering to various user needs [7][20] - The pricing of large model all-in-one machines is influenced by four main factors: hardware performance, system integration capabilities, industry customization services, and compliance with security delivery [30] Definition and Composition - Large model all-in-one machines are integrated AI infrastructure designed to support the entire lifecycle of large model development, training, deployment, and operation, typically comprising software, hardware, and operational support [14] Deployment Characteristics - The deployment of large model all-in-one machines emphasizes extreme performance, local data closure, and high controllability, making them suitable for scenarios with high real-time and data security requirements [19] Major Manufacturers and Product Pricing - Major manufacturers in the market include Huawei, Inspur, and Unisplendour, with products offering diverse configurations and functionalities [20][21] - The price range for these products varies significantly, with high-end models supporting ultra-large model training and inference, while mid-range and basic models cater to mainstream applications and lightweight model inference [22][27][28] User Profile - The target users for large model all-in-one machines are typically small to medium-sized enterprises lacking professional AI infrastructure and teams, requiring local deployment and quick setup [36][37]