Ping An CSI Artificial Intelligence ETF (512930) Rises 2.24%; SSE Releases Document on AI Large Model Enterprises Applying the Fifth Set of Listing Standards of the Science and Technology Innovation Board

NewTimeSpace (newtimespace.com) News, As of 09:53 AM on June 18, 2026, the CSI Artificial Intelligence Theme Index (930713) rose strongly by 2.11%, and Ping An CSI Artificial Intelligence ETF (512930) advanced by 2.24%, driving toward a 5-day consecutive winning streak. Its latest price was quoted at RMB 0.73. Looking at a longer time horizon, as of June 17, 2026, Ping An CSI Artificial Intelligence ETF recorded a cumulative gain of 5.31% over the past week, ranking 2nd out of 4 comparable funds in terms of growth.

Wind data shows that leveraged capital continues to position itself in the market. The latest margin buying amount of Ping An CSI Artificial Intelligence ETF reached RMB 4.7916 million, bringing its latest margin balance to RMB 48.9956 million.

On the news front, on June 17, the Shanghai Stock Exchange (SSE) issued the Application Guidelines No. 10 for Issuance and Listing Review Rules of the Shanghai Stock Exchange—Application of the Fifth Set of Listing Standards of the Science and Technology Innovation Board by Artificial Intelligence Large Model Enterprises. The document aims to further standardize the application of the fifth set of listing standards for tech-centric enterprises on the Science and Technology Innovation Board (STAR Market), better supporting high-quality AI large model enterprises that have not yet formed a certain revenue scale to apply these standards, and accelerating the innovative development of artificial intelligence.

SDIC Securities (Hong Kong) stated that China's AI industry is undergoing a historic turning point from technological catching-up to commercial monetization, shifting focus from pursuing technology to application implementation, thereby realizing the realization of profits. Three major factors are interacting concurrently: first, declining costs, with domestic token prices plunging by 99% over the past two years; second, policy support, where new policies were rolled out every single month from January to May this year, sending a clear signal of moving beyond mere encouragement to actual implementation; third, technological maturity, as Agents are no longer just a laboratory concept, but have become mature products that can be deployed by enterprises and generate actual revenue.

Hong Kong-listed Large Model Concept Stocks:

KNOWLEDGE ATLAS (02513.HK)

Knowledge Atlas Technology Joint Stock Company Limited (02513.HK; commercially known as Zhipu AI) is a leading player in China's independent large language model (LLM) sector (recognized for its capabilities and market position by Frost & Sullivan). The company has released its next-generation flagship model, GLM-5, achieving open-source State-of-the-Art (SOTA) performance in coding and agentic capabilities. It has also open-sourced the multimodal image generation model GLM-Image in collaboration with Huawei. Focusing on novel model architecture design, generalized reinforcement learning paradigms, and autonomous model evolution, its business layout closely aligns with the trend of enterprise-level AI productivity transformation.

MINIMAX-W (00100.HK)

A top-tier player dedicated to omni-modal Artificial General Intelligence (AGI). The company continuously iterates its video generation model matrix and has partnered with mainstream domestic and overseas chip manufacturers and inference platforms to complete underlying adaptations. The total monthly active users (MAU) of its B2C and B2B LLM applications, along with multimodal API call volumes, maintain rapid growth, further broadening its computing power ecological layout.

MININGLAMP-W (02718.HK)

As an LLM concept stock, the company fully underpins its Agentic AI positioning with its self-developed edge models—Mano, Cito, and Mano-P—alongside the Cider inference framework. Its business architecture utilizes the DeepMiner LLM as the underlying engine and Octo as the collaborative hub, uniformly delivering various AI products and industry solutions in the form of Agentic Services. Mininglamp pursues a differentiated technological route, bypassing the parameter expansion of general models in favor of a "Scaling Out" approach that coordinates multiple specialized small models. Its core moats do not rely on parameter scale, but rather on granular scenario data, specialized models, and continuous learning. This enables it to achieve a level of precision in vertical scenarios that general models cannot match, as it remains committed to building an open-source, privately deployable, and white-box auditable Private AI infrastructure.

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