Large Model Concept Stocks Watch | MINIMAX-W (0100.HK) Surges Over 10% in Morning Session, Company Discloses Its Latest Technical Progress in Cost Reduction and Efficiency Enhancement for Million-Text Tokens

NewTimeSpace (newtimespace.com) News, On July 15, 2026, Hong Kong-listed AI agent concept stocks rallied collectively, with stocks such as MINIMAX-W (0100.HK), Zhipu (2513.HK), and Mininglamp Technology (2718.HK) delivering stellar performances. As of 10:20, MINIMAX-W (0100.HK) was quoted at HK$257.000, leading the gains among a crowd of large model concept stocks with an 11.74% surge.

In terms of news coverage, on July 14, on the eve of the 2026 World Artificial Intelligence Conference (WAIC) & High-Level Conference on Global AI Governance, MiniMax disclosed its latest technical progress: through its self-developed Mixed Sparse Attention (MSA) architecture, the company successfully reduced the per-token computing cost for million-word long texts to approximately 1/20 of that of traditional full attention mechanisms, attempting to forge a breakthrough path of cost reduction and efficiency enhancement in the global large model race.

Industrial Securities stated that the current round of AI represents a general-purpose, underlying technological innovation characterized by a longer industrial penetration cycle, broader market space, and stronger growth sustainability. At the same time, global capital investments in AI continue to ramp up, and the resonance of capital expenditure supports the accelerated upward trajectory of industry prosperity. Furthermore, from a penetration rate perspective, the current AI penetration rate is only equivalent to the internet penetration rate in 1998, which also indicates that the industrial development remains mid-course and has not yet finished the steepest phase of its growth slope. Finally, at the policy level, technology growth fields such as AI enjoy two-way support from both domestic and international policies, solidifying the industry's foundation while further opening up medium-to-long-term growth space.

Hong Kong-listed Large Model Concept Stocks:

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.

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.

MININGLAMP-W (02718.HK)

As an LLM concept stock, Mininglamp Technology is recognized by the market as the "First Agentic AI Stock in Hong Kong." Its self-developed model cluster includes the DeepMiner LLM product line (underlying engine), models such as Mano/Cito, and the Cider inference acceleration framework. These are all interconnected by the Octo platform layer to serve as a human-Agent collaboration hub, ultimately delivered in the form of Agentic Services to empower the implementation of decision-making agents in industries like marketing and mass consumption. The company bypasses the "Scaling Up" route of monolithic LLMs, opting instead for a "Scaling Out" approach through the collaboration of multiple specialized small models, achieving precision that surpasses general models in vertical scenarios. Its core moats lie in granular scenario data, specialized models, and continuous learning, culminating in an open-source, privately deployable, and white-box auditable Private AI infrastructure.

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