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<a href="/company/anta">Anta Sports</a> delivered results that were largely well received by the market. In the first half of 2026, the group’s revenue rose 12.9% year-on-year (YoY) to RMB 43.5 billion (USD 6.5 billion), marking the first time its first-half revenue exceeded RMB 40 billion (USD 5.9 billion). Overall gross margin increased 0.5 percentage points to 63.9%, while operating profit climbed 16.1% to RMB 11.8 billion (USD 1.8 billion). Its operating margin rose to 27%, the highest level for a first half in nearly seven years.
Anta Group co-CEO Lai Shixian said at the earnings briefing that performance was broad-based across its brands. Growth at the Anta brand and its other brands exceeded the full-year guidance set at the beginning of the year, while Fila China reached the upper end of its guidance range. Lai said the results reflected the advantages of the group’s multibrand portfolio.
CFO Bi Mingwei added that the group maintained steady profitability even as revenue exceeded RMB 40 billion. Excluding the one-off gain from the placement of Amer Sports shares, profit attributable to shareholders was about RMB 7.9 billion (USD 1.2 billion), up 12.9% YoY.
The market reacted positively. On the day the results were released, Anta Sports shares closed at HKD 78.75 (USD 10), up 9.53%, lifting its market capitalization back above HKD 220 billion (USD 28.1 billion).
A breakdown by brand shows a more nuanced picture.
Revenue at the core Anta brand rose 4.8% YoY to RMB 17.8 billion (USD 2.6 billion). Operating profit increased 1.2% to RMB 4.0 billion (USD 593.8 million), while operating margin slipped to 22.5% from 23.3% a year earlier.
During the reporting period, the brand recorded growth in several key product categories. Sales of four running shoe lines, PG7, C Family, Mach, and Zone 2, exceeded 5.6 million pairs in the first half, up more than 30% YoY. In apparel, sales of products including Storm Mecha surpassed two million units, an increase of nearly 35%.
Lai said the Anta brand is becoming more focused in its product strategy, with a greater emphasis on professional sports products. At the same time, a higher mix of <a href="/industry/e-commerce">e-commerce</a> and directly operated retail weighed on margins.
In July, former Anta brand CEO Tsui Yeung left the company for family reasons. Seven store formats he had championed, including Anta Super Store, Anta Sneakerverse, and Anta Arena, are still being tested.
As of June 30, the core Anta brand, excluding Anta Kids, had 7,122 stores, down 81 from the end of 2025. Lai said at the earnings briefing that the ultimate measure of channel reform was not how many stores were opened, but whether products could reach consumers more effectively through the right channels.
The comment suggests the company is placing greater emphasis on channel effectiveness after two years of retail experimentation.
Overseas markets, meanwhile, have become an increasingly important growth area for the core brand.
Anta’s overseas revenue rose 35% YoY in the first half. According to the company, the group is advancing a plan to operate as many as 1,000 stores in Southeast Asia. In North America, Anta has also opened its first flagship store in Los Angeles and is working with retailers including Foot Locker, DSG, and JD Sports.
The overseas growth, however, comes from a relatively small base. Expanding toward 1,000 stores in Southeast Asia will also require sustained investment, leaving uncertainty around both the pace of Anta’s international expansion and its returns.
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Fila presented a different picture. In the first half, revenue rose 6.1% YoY to RMB 15.1 billion (USD 2.2 billion). Operating profit increased 9.7% to RMB 4.3 billion (USD 638.4 million), while operating margin rose one percentage point from a year earlier to 28.7%.
Over the past two years, Fila has centered its business on the “One Fila” strategy and expanded its presence in sports including tennis and golf. The simultaneous increase in revenue and margin suggests the strategy is contributing to improved profitability.
Within Fila, apparel has again become a growth driver. Women’s apparel increased its share by 2 percentage points to more than 40%.
Fila has long been associated with premium sports fashion. Footwear, however, remains an important category for sportswear brands seeking to demonstrate product technology, and Fila has made fewer visible gains in this area.
Anta’s “other brands” segment, led by Descente and Kolon Sport, continued to record strong growth. Revenue rose 44.2% year over year to RMB 10.7 billion (USD 1.6 billion), surpassing RMB 10 billion (USD 1.5 billion) in a half-year reporting period for the first time. Operating profit reached RMB 3.5 billion (USD 519.6 million), up 43.9%.
Beyond its multibrand strategy, Anta Sports’ investment in <a href="/industry/ai">artificial intelligence</a> emerged as another focus of its results.
Lai said the group is advancing an “AI 365” strategy. Its self-developed Linglong design model can reportedly turn a sketch into a design rendering in 15 seconds, while its Lingxi styling model has been deployed in retail stores to recommend outfits for different scenarios and provide virtual try-ons.
Anta said it is also using AI in corporate management to analyze social media and consumer trends in support of market forecasting and inventory management. During the reporting period, the group’s R&amp;D spending amounted to 2.5% of revenue.
The company is expanding the use of AI across areas ranging from design to retail and customer service, although it remains too early to determine how much those tools will improve operating efficiency.
Lai said the initiative was still at an early stage and that its value would ultimately need to be measured through better products, faster responses, healthier inventory, and an improved consumer experience.
Those are also areas that will remain important as growth in the broader sportswear market becomes more difficult to sustain.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3957560779292037">article</a> was written by Xie Yunzi for 36Kr.
Note: HKD, RMB figures are converted to USD at rates of HKD 7.84 = USD 1 and RMB 6.74 = USD 1 based on estimates as of August 31, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Anta’s multibrand strategy continues to deliver in H1 2026 as its AI ambitions take shape

East Asia

China

Retail

Consumer Economy

Guming Holdings, which operates the GoodMe tea chain, reported its 2026 interim results on the evening of August 26. In the first half of the year, revenue rose 31.9% year-on-year to RMB 7.47 billion (USD 1.1 billion), while adjusted profit increased 44.4% to RMB 1.57 billion (USD 233.1 million).
The results came as competition remained intense in China’s new-style tea beverage market. With profit growing faster than revenue, the figures suggest Guming made progress in controlling costs and improving operating efficiency while continuing to expand.
GoodMe stores generated average daily gross merchandise value (GMV) of RMB 7,800 (USD 1,158) per store in the first half, broadly unchanged from a year earlier. Total store GMV reached RMB 19.7 billion (USD 2.9 billion), up 40.1% year-on-year.
GoodMe has also reported improving store performance since the start of 2026, supported by new product launches, marketing initiatives, and investment from its franchisees.
In the first half, the company continued to invest in product R&amp;D and regularly introduced new items. GoodMe launched 51 drinks during the reporting period. Several products, including its “Kujin Ganlai Latte,” gained traction with consumers, according to the company.
GoodMe also introduced a 30-day freshness standard for coffee beans across its stores, limiting the period from roasting to in-store use to 30 days. The initiative forms part of its broader effort to improve product quality while maintaining relatively affordable pricing.
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According to its financial report, Guming uses its own cold chain warehousing and logistics infrastructure to store and transport perishable ingredients including fresh fruit, tea leaves, and fresh milk. It has also established supply chain management standards covering procurement, ingredient processing, warehousing, and store delivery.
As of June 30, the company operated 24 warehouses with a combined gross floor area of 277,000 square meters and more than 82,000 cubic meters of cold storage capacity. About 73% of its stores were within 150 kilometers of a warehouse, while 99% could receive deliveries every two days. Warehouse-to-store delivery costs were kept below 1% of total GMV, according to the company.
GoodMe had 14,351 stores in the first half, up 28.4% from 11,173 a year earlier. As beverage chains expand, opening additional stores can increase the risk of cannibalizing sales at existing locations. GoodMe, however, has continued to expand its network while improving the efficiency of its logistics operations.
Another area to watch is GoodMe’s gradual expansion into higher-tier cities after years of focusing on lower-tier markets in China.
In August, GoodMe opened its first store in Nanjing. According to company data, the store recorded peak daily sales of RMB 160,000 (USD 23,753.7) during its first three days of operation, with its highest single-day volume exceeding 9,000 cups.
Guming executives have repeatedly said the brand does not plan to enter Shanghai or Beijing in the near term. The company has said higher-tier cities tend to have a larger share of delivery orders, while higher rents and labor costs make it more difficult for existing product prices to cover operating expenses.
The Nanjing opening nevertheless gives GoodMe a way to test whether its store model can translate to more expensive urban markets.
Nanjing, a major city in East China and a market closer to GoodMe’s geographic roots, offers a relatively measured entry point as the company explores higher-tier cities.
Whether GoodMe can replicate its store-level economics in those markets will depend in part on whether categories such as coffee can lift average spending per order and repeat purchases. It will also depend on whether further supply chain efficiencies can offset the higher costs of operating in larger cities.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3957195146247559">article</a> was written by Yang Shuo for 36Kr.
Note: RMB figures are converted to USD at rates of RMB 6.74 = USD 1 based on estimates as of August 31, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

GoodMe pushes beyond lower-tier markets with efficiency gains in hand

There was no live stream, and CEO Lei Jun did not make an appearance. Yet <a href="/company/xiaomi">Xiaomi</a> needed just 40 minutes to unveil three chips.
On August 24, Xiaomi launched three Xring chips at once: the flagship Xring O3 system-on-chip (SoC), the Xring O100 <a href="/industry/ai">artificial intelligence</a> accelerator, and the high-compute Xring D100 AI chip for smart driving.
In recent years, smartphone makers developing chips in-house have typically focused on specialized functions such as imaging, communications, and power management. But as large AI models move into smartphones, cars, and robots, on-device AI capabilities are becoming a more important focus of chip investment.
AI models are also growing larger. Delivering more computing power while overcoming memory-related constraints has become a central challenge for the next generation of AI chip design.
The Xring O3 is Xiaomi’s second flagship SoC developed in-house. It retains a 3-nanometer process, while its transistor count has increased to 24 billion from 19 billion in the previous generation.
One notable change is the O3’s greater emphasis on AI computing. In addition to a neural processing unit (NPU) dedicated to AI tasks, Xiaomi has added acceleration units across several major chip modules to handle AI workloads of different sizes.
The design is intended to reduce the efficiency losses and excess power consumption that can result when lightweight AI tasks repeatedly call on the NPU.
According to details disclosed at the launch, the Xring O3 will debut in September with the Xiaomi 18 Fold.
Compared with the O3, the Xring O100 more directly reflects changes in AI chip design. In recent years, computing performance has been one of the most commonly cited measures of chip competitiveness. But as the parameter counts of large models increase, computing power is no longer the only constraint on how quickly those models can run.
Compute units are becoming more powerful, but they must constantly retrieve model parameters and intermediate data from memory. If data transfer speeds cannot keep pace, the compute units are left waiting. The result is a growing imbalance in AI chips: computing capacity continues to rise, while memory bandwidth and data transfer capacity are emerging as key bottlenecks.
Apple, <a href="/company/huawei">Huawei</a>, and Xiaomi have each pursued architectural approaches aimed at addressing the problem.
Apple has increased the capacity and bandwidth of its unified memory architecture, which allows the CPU, GPU, and its Neural Engine to access shared memory. Huawei has also expanded high-bandwidth memory capabilities in its AI chips.
Xiaomi’s Xring O100 AI accelerator uses a near-memory computing architecture designed for on-device AI. The design vertically stacks compute and memory units, or places them physically closer together, to reduce the latency caused by moving data between them.
The chip uses 3D wafer-on-wafer stacking. Through hybrid bonding technology, two DRAM wafers and one NPU compute wafer are bonded together.
The Xring O100 offers memory bandwidth of 1.22 terabytes per second and integrates a 14-core NPU designed for large AI models. Xiaomi said ultra-dense interconnects between its compute and memory units enable on-device large-model inference at speeds of up to 330 tokens per second.
At the launch, Xiaomi demonstrated prototype devices equipped with the Xring O100 and Xring O3. Running offline on Xiaomi’s MiMo large model, the devices generated output with little apparent delay during the demonstration.
As more AI tasks are performed directly on devices, hardware such as smartphones, PCs, and cars faces growing demands for real-time performance, privacy, and offline functionality.
The day after Xiaomi’s chip launch, Apple also introduced its next-generation M6 and M5 Ultra chips. The M6 uses a 2-nm process and is designed for office work, software development, content creation, and on-device AI tasks. The M5 Ultra, meanwhile, uses a new multi-chip packaging architecture intended to improve performance, memory capacity, and local AI capabilities.
For its automotive business, Xiaomi also launched the Xring D100, an in-house 3-nm AI chip designed for intelligent driving. It contains a 20-core CPU and a 16-core NPU. According to Xiaomi, a single chip supports up to 160 gigabytes of memory and can run models with more than 200 billion parameters locally.
The Xring D100 also supports multi-chip computing. Xiaomi said the chip can provide local AI computing capacity for complex workloads and can also be used in vehicles to run intelligent-driving algorithms.
The latest release marks Xiaomi’s biggest chip push since it began developing semiconductors in-house in 2016.
Xiaomi initially shifted toward smaller, specialized chips before restarting development of a flagship SoC in 2021. In 2025, it launched its first Xring flagship chip, the Xring O1. One year later, it has introduced three more chips across smartphones, AI computing, and automotive applications.
Xiaomi has reportedly invested more than RMB 18 billion (USD 2.7 billion) in chip development over the past five years and allocated a total budget of RMB 50 billion (USD 7.4 billion). Its chip R&amp;D team currently has more than 3,000 employees.
As on-device AI adoption accelerates, chips will become an increasingly important foundation for Xiaomi’s smartphone, automotive, and <a href="/industry/robotics">robotics</a> businesses. The company has said its in-house chip strategy will therefore focus on on-device AI inference.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3955789065158018">article</a> was written by Xiao Man for 36Kr.
Note: RMB figures are converted to USD at rates of RMB 6.74 = USD 1 based on estimates as of August 31, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Xiaomi doubles down on in-house chips with Xring O3, O100, and D100

Artificial Intelligence

Deep Tech

Semiconductors

AI Infrastructure

Ahead of the US market open on August 25, Vipshop released its financial results for the second quarter of 2026. The company generated RMB 24.7 billion (USD 3.7 billion) in net revenue, while non-GAAP net income fell to RMB 392 million (USD 58.2 million) from RMB 2.1 billion (USD 311.8 million) a year earlier, mainly because of a one-time withholding tax adjustment related to historical dividend distributions.
According to its earnings report, Vipshop recognized about RMB 1.56 billion (USD 231.6 million) in withholding tax expenses in the second quarter related to historical dividend distributions from mainland China to Hong Kong.
Vipshop CFO Mark Wang said the adjustment related to dividend distributions remitted in prior years and was expected to be settled in the third quarter. Going forward, the company will continue to accrue dividend withholding tax at the statutory rate for onshore earnings allocated for offshore repatriation.
Wang added that the adjustment would not affect operating margins or pretax cash flows, while its impact on future net margin was expected to be minimal.
In its core business, Vipshop recorded gross merchandise value (GMV) of RMB 50.6 billion (USD 7.5 billion) in the second quarter, with 182 million orders. Its Super VIP (SVIP) membership base continued to grow and has now surpassed ten million users.
During the quarter, Vipshop expanded exclusive merchandise offerings for SVIP members through initiatives including SVIP private sales and SVIP trial offers. It also increased members’ access to differentiated products and pricing benefits as part of efforts to improve the experience for high-value users.
Vipshop’s Super Brand Day and Super Product Category Day campaigns both maintained double-digit year-over-year growth in the second quarter, while active SVIP users continued to account for more than 50% of the platform’s online sales.
A China Merchants Securities research report said Vipshop has built a stable core base of SVIP users by offering authentic branded goods at competitive prices, alongside services such as free returns and exchanges. Growth in both the core user base and its contribution to GMV supports the company’s long-term development, the brokerage said.
Across the first half of the year, Vipshop introduced a new series of campaigns built around different shopping occasions. The company used scenario-based merchandising to promote trend-driven categories including sports products and gifts.
Its Kuangmiao section continued to introduce well-reviewed products at deep discounts, helping increase sales through the section as well as repeat visits from users.
Vipshop also expanded its use of <a href="/industry/ai">artificial intelligence</a> across its operations. On the customer side, the company had previously introduced AI-enabled services including virtual try-on and intelligent customer service. In management and operations, Vipshop is moving from individual AI tools toward a platform spanning its major business systems.
The company has also reported improvements in supply chain management and day-to-day operations from the initiative.
Improvements in product mix, membership services, and user experience have helped increase transaction value on the platform. In the first half of 2026, Vipshop returned nearly USD 400 million to shareholders through dividends and share repurchases.
China Merchants Securities said Vipshop is expected to return at least 75% of its 2025 non-GAAP net income attributable to shareholders through annual dividends and share repurchases in 2026. The company continued repurchasing shares in the second quarter, which the brokerage said reflected confidence in its long-term operations and management’s focus on shareholder interests.
Alongside its second-quarter results, Vipshop’s board approved a new share repurchase program authorizing the company to buy back up to USD 1 billion of its American depositary shares or Class A ordinary shares within 24 months of completing its existing repurchase program.
Looking ahead, a Huatai Securities research report said Vipshop has strengthened its position among core consumers and increased its share of their spending by improving the SVIP service experience and differentiating its product supply. The brokerage added that continued shareholder returns could provide some support for the company’s valuation. Huatai Securities maintained its “buy” rating on Vipshop.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3954812220685440">article</a> was written by 36Kr Caijing.
Note: RMB figures are converted to USD at rates of RMB 6.74 = USD 1 based on estimates as of August 31, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Vipshop’s membership base tops ten million as buybacks and dividends continue

On-demand Services

E-commerce

… to be opening up, according to their operators.
At its earnings briefing earlier this month, SGX revealed a slate of about 50 companies at "various stages of engagement and preparation" for IPOs, without naming them. A third of this batch are in tech, advanced manufacturing, and digital infrastructure; another third in the consumer and healthcare sectors and the rest include players in real estate, the exchange said.
"A year ago we said, at least 30 [IPOs], right? And I can tell you it's comfortably above that now," SGX's Syn told Nikkei Asia. "It's not just a list on an Excel sheet. It's people who paid money to professionals to start work [toward a listing], and that is what we call a pipeline."
SGX also had a major listing last month. Medical services provider <a title="" href="https://asia.nikkei.com/business/markets/ipo/singapore-hospital-group-makes-market-debut-as-population-ages" target="_blank" rel="noopener">Foundation Healthcare Holdings</a> raised SGD 242 million (USD 190.5 million) through its IPO.
The Thai bourse has disclosed a near-term pipeline of ten companies for IPOs, five of which have already been approved and five that are under review. The exchange expects the total number of new listings across its main and secondary boards this year to at least match the 18 reached last year.
"From our perspective, what we can control is to make sure that our regulations are competitive," SET's Asadej said. "Often, if the businesses are based in Thailand and revenues are based in Thailand, in the longer run, it makes more sense for them to list in Thailand."
This article first appeared on <a href="https://asia.nikkei.com/business/markets/trading-asia/thailand-singapore-exchanges-seek-tech-listings-as-ai-booms">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.kr-asia.com/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.
Note: SGD, THB figures are converted to USD at rates of SGD 1.27 = USD 1 and THB 32.70 = USD 1 based on estimates as of August 25, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Thailand, Singapore exchanges seek tech listings as AI booms

Investment

Singapore

Thailand

Southeast Asia

… existing ones. Unitree was 8,000 times oversubscribed by retail investors. That demand exists. Perpetuals just give international capital a way to participate in a mania that's already happening."
This article first appeared on <a href="https://asia.nikkei.com/business/markets/global-investors-use-perp-bets-to-chase-china-tech-stocks-like-unitree">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.kr-asia.com/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.

Global investors use "perp" bets to chase China tech stocks like Unitree

… src="https://console.kr-asia.com/wp-content/uploads/2026/08/Galbot-Wang-He-World-Robot-Conference-2026-Presentation.jpg" alt="" width="1920" height="1080" srcset="https://console.kr-asia.com/wp-content/uploads/2026/08/Galbot-Wang-He-World-Robot-Conference-2026-Presentation.jpg 1920w, https://console.kr-asia.com/wp-content/uploads/2026/08/Galbot-Wang-He-World-Robot-Conference-2026-Presentation-720x405.jpg 720w, https://console.kr-asia.com/wp-content/uploads/2026/08/Galbot-Wang-He-World-Robot-Conference-2026-Presentation-1024x576.jpg 1024w, https://console.kr-asia.com/wp-content/uploads/2026/08/Galbot-Wang-He-World-Robot-Conference-2026-Presentation-768x432.jpg 768w, https://console.kr-asia.com/wp-content/uploads/2026/08/Galbot-Wang-He-World-Robot-Conference-2026-Presentation-1536x864.jpg 1536w, https://console.kr-asia.com/wp-content/uploads/2026/08/Galbot-Wang-He-World-Robot-Conference-2026-Presentation-480x270.jpg 480w" sizes="(max-width: 1920px) 100vw, 1920px" /><figcaption id="caption-attachment-163828" class="wp-caption-text">Photo source: Galbot.</figcaption></figure>
The second condition may prove just as important as the first.
Even when a model can perform much of a task, customers may still need algorithm engineers to collect robot motion data, label it, and debug the resulting behavior. That adaptation cost can make deployment difficult for smaller businesses and individual users.
For embodied intelligence to reach a mass market, teaching a robot also has to become substantially easier.
During his presentation, Wang introduced WAM-TTT, a test-time training approach intended to address that problem.
Under the approach, a user wears a first-person camera and records themselves doing a job. The model can use that unlabeled video to adapt to the task without requiring a fresh round of robot motion data collection, according to Galbot.
The foundation model supplies general knowledge about the physical world. A person demonstrates the specific work to be done.
If that process becomes reliable, adapting a robot could begin to look less like an engineering project and more like teaching a new worker.
At the end of his presentation, Wang outlined a longer-term vision in which robots could eventually approach smartphone-scale shipment volumes while retaining product values closer to automobiles and the continuous upgradeability of software.
A model improvement could then be distributed across a large installed base of robots.
The scale of that opportunity remains hypothetical, but the underlying problem is already clear.
Humanity spent decades generating the language, images, and other data that now train models for the digital world. Comparable training data for the physical world is far less abundant.
Robots will have to help generate it themselves by identifying products in pharmacies, responding to disruptions in factories, manipulating unfamiliar objects, and learning jobs from human demonstrations.
Each deployment can become another source of experience for the model.
The ChatGPT moment for embodied intelligence, by Wang’s definition, will arrive only when that accumulated intelligence can transfer across different robot bodies and when teaching a robot a new skill becomes simple enough for ordinary people to do.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3946454123822213">article</a> was written by Xiao Xi for 36Kr.

Is the frontier of humanoid robotics shifting from hardware to intelligence?

Robotics

Embodied Intelligence

… 28, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Can Lord of Mysteries become Kuaishou’s gaming breakout?

Kuaishou

Gaming

Creative

… data-tmfx-note="1">Note: RMB figures are converted to USD at rates of RMB 6.74 = USD 1 based on estimates as of August 28, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

JD.com wants to build the infrastructure robots still lack

JD.com