Daily Report on Hong Kong-Listed LLM Concept Stocks (May 26, 2026)
I. Industry Observations
NewTimeSpace (newtimespace.com) News: According to Wind data, on May 26, 2026, the three major Hong Kong stock indices closed mixed. The Hang Seng Index (HSI) fell 0.03% to close at 25,599.45 points, the Hang Seng Tech Index rose 1.59% to close at 4,946.88 points, and the Hang Seng China Enterprises Index (HSCEI) rose 0.31% to close at 8,576.89 points. The total market turnover for the full day was HKD 359.476 billion, representing a significant increase compared to the previous trading day. Southbound capital recorded a net sell-out of HKD 968 million.
The AI industrial chain continued to explode. Mininglamp Technology-W surged by 18.95%, Zhipu rose by 4.91%, while stocks such as Xunce, SenseTime-W, and baba-W followed the upward trend. Lenovo Group continued its sharp rally, rising 15.5% as the company's financial results significantly beat market expectations, with its full-year AI-related revenue doubling year-on-year. 51World continued to surge by 27.55% following the official launch of its embodied AI data platform, Aperdata.ai.
II. Market Performance of LLM Concept Stocks
|
Stock Code |
Stock Name |
Closing Price (HKD) |
Change (%) |
|
02718.HK |
MINIMAX-W |
313.800 |
18.95 |
|
02513.HK |
KNOWLEDGE ATLAS |
1345.000 |
4.91 |
|
03317.HK |
XUNCE |
247.400 |
2.49 |
|
00020.HK |
SENSETIME-W |
1.790 |
1.13 |
|
09988.HK |
BABA-W |
127.600 |
0.47 |
|
01024.HK |
KUAISHOU-W |
45.800 |
0.35 |
|
00100.HK |
MINIMAX-W |
769.000 |
0.07 |
|
09888.HK |
BIDU-SW |
128.000 |
-0.16 |
|
00700.HK |
TENCENT |
439.000 |
-0.54 |
|
03690.HK |
MEITUAN-W |
78.800 |
-3.13 |
Data Source: HKEX. For reference only, not investment advice. Data as of market close on May 26, 2026.
III. Industry and Corporate Dynamics
According to calculations based on the latest data from OpenRouter, the total invocation volume of global AI large models reached 28.9 trillion tokens last week (May 18 to May 24), a week-on-week increase of 7.4%. This marks the fifth consecutive week of growth, indicating that the invocation demand for large models is continuing to release. Among the listed AI large models, the weekly invocation volume of Chinese AI large models reached 9.223 trillion tokens, representing a quarter-on-quarter increase of 19.89%. During the same period, the weekly invocation volume of US AI large models was 4.93 trillion tokens, a quarter-on-quarter increase of 16.27%.
Regarding international AI giants, on Wednesday local time, it was reported that Anthropic disclosed to investors in its latest round of financing that its revenue for the second quarter of 2026 is expected to reach USD 10.9 billion, an increase of approximately 127% compared to USD 4.8 billion in the first quarter, and it is expected to realize an operating profit of USD 559 million for the first time.
In the early morning of May 26, CodeArena, a globally authoritative third-party programming leaderboard, released its latest rankings. Alibaba's latest flagship model, Qwen3.7-Max, scored 1,541 points, surpassing a series of models including GPT-5.5, Gemini-3.5-Flash, GLM-5.1, and Kimi-K2.6. It ranks second globally among large model vendors, trailing only the Claude series. This also signifies that Qwen 3.7 has successfully entered the first tier of global programming models in the field of code comprehension and generation.
IV. Introduction to LLM Concept Stocks
|
Stock Name |
Stock Code |
LLM Products & Business Profile |
|
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 |
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 |
Relying on its self-developed edge models Mano, Cito, and Mano-P, along with the Cider inference framework, it fully supports its Agentic AI positioning. Its business architecture uses 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 "Scaling Up" parameter expansion of general models in favor of a "Scaling Out" approach that coordinates multiple specialized small models. Its core moats are granular scenario data, specialized models, and continuous learning, achieving precision in vertical scenarios that general models cannot match. The company is committed to building an open-source, privately deployable, and white-box auditable Private AI infrastructure. |
|
BABA-W |
09988.HK |
The company has released several new models, including Qwen3.6-Plus, with the Qwen LLM surpassing 1.4 trillion Tokens in daily API calls, setting a new global record for daily calls on third-party platforms. The Qwen consumer-facing application has exceeded 300 million MAU and has been integrated into the smart cabins of multiple automakers. It consistently ranks at the forefront in international benchmark evaluations for coding and agentic capabilities. Its business layout seamlessly matches the trend of scaled procurement of computing power and model APIs by government and enterprise clients. |
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