IDC released a global commercial service robot report, showing that Chinese manufacturers accounted for over 90% of shipments.
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According to reports, global shipments of commercial service robots will reach 454,000 units by 2030, with a market size of $3.17 billion.
Mars Finance reported on July 7th that the latest "Worldwide Delivery Robots Tracker" and "Worldwide Commercial Cleaning Robots Tracker" reports released by International Data Corporation (IDC) show that the global commercial service robot market continued its rapid growth in 2025. The market size reached $1.37 billion, a year-on-year increase of 35.7%; shipments totaled approximately 155,000 units, a year-on-year increase of 44.1%. IDC predicts that the global commercial service robot market will continue to grow rapidly from 2026 to 2030, with a compound annual growth rate (CAGR) of approximately 15.1%. By 2030, global shipments of commercial service robots are expected to reach 454,000 units, with a market size of $3.17 billion. (Wide Angle Observation)
NAVIAI humanoid robots have been officially commercialized in multiple scenarios, covering industries, services, education, and other fields.
Mars Finance reported on July 2nd that Zhejiang Humanoid Robot Innovation Center Co., Ltd. announced that its NAVIAI humanoid robot has been deployed on a large scale in four major fields: industrial manufacturing, life services, industry-education integration, and data acquisition, and has officially entered commercial use. Relying on its self-developed SPIRE intelligent system and supporting development toolchain, NAVIAI can achieve precision operation at the ±0.02 mm level, capable of handling industrial tasks such as chemical experiments, production line sorting, parts assembly, and garment sewing, with a core process success rate of up to 99.99%. Currently, it has partnered with over 50 universities and colleges, establishing more than 10 training bases; the supporting data acquisition system supports the robot's continuous optimization capabilities. (Wide Angle Observation)
Xu Xiaolan, President of the Chinese Institute of Electronics: my country's humanoid robot exports increased by 210%, accelerating their entry into industrial production lines.
According to Mars Finance, at a press conference for the 2026 World Robot Conference today, Xu Xiaolan, a member of the Standing Committee of the National Committee of the Chinese People's Political Consultative Conference (CPPCC), Vice Chairman of the Central Committee of the China Zhi Gong Party, and Chairman of the Chinese Institute of Electronics, introduced that my country has been the world's largest industrial robot market for 13 consecutive years, with domestically branded industrial robots accounting for over 50% of the domestic market share. my country possesses a complete industrial chain supporting humanoid robots, encompassing materials, core components, system integration, scenario operation, and data services. In 2025, with 90% of global shipments and over 330 product models, China firmly holds a leading position in the global humanoid robot industry. Data from the first quarter of 2026 shows that my country's exports of humanoid robots increased by 210% year-on-year, becoming a new calling card for China's high-end manufacturing exports. The application scenarios for humanoid robots are rapidly expanding from entertainment, marketing, and education to industrial scenarios such as 3C quality inspection, logistics sorting, and automobile manufacturing. Humanoid robots have initially acquired the capability to be integrated into industrial production lines. (Reporter Li Mingming, Science and Technology Innovation Board Daily)
The positive earnings forecast in the interim report signals a profit inflection point, and the humanoid robot sector is ushering in a new era of industry synergy.
On July 7th, the A-share humanoid robot sector experienced a correction after a rapid rise, with the Wind Humanoid Robot Concept Index falling 2.93% that day. Currently, the industry fundamentals are undergoing profound changes: multiple companies in the industrial chain have released preliminary earnings announcements for the first half of the year, showing improved profitability trends from core components to complete machine integration; simultaneously, leading global companies are accelerating mass production, with capacity construction and order verification entering a critical window period. Analysts believe that the humanoid robot industry is gradually shifting from the initial concept-driven phase to a new stage of capacity implementation and performance realization. Coupled with multiple factors such as the IPOs of leading companies and the accelerated commercialization of leading domestic and international manufacturers, the medium- to long-term investment logic of the sector is receiving strong support from fundamentals. The short-term correction may be a normal digestion of the previous gains by the market. With the profit inflection point approaching in each link of the industrial chain, the humanoid robot sector is expected to usher in a new development stage of resonance both domestically and internationally. (China Securities Journal)
Goldman Sachs: The global humanoid robot market will grow from approximately 20,000 units in 2025 to 1.4 million units in 2035.
According to Mars Finance, Goldman Sachs stated that another path for AI to enter the real world is through robots, autonomous driving devices, drones, and intelligent industrial equipment. Goldman Sachs calls this "physical AI," which is far more challenging than text generation models because machines must not only understand language and images but also handle gravity, friction, materials, temperature, motion trajectories, and safety constraints. Humanoid robots are the most anticipated area. Goldman Sachs predicts that the global humanoid robot market will grow from approximately 20,000 units in 2025 to 1.4 million units in 2035. This demand is based on labor shortages: the US manufacturing sector employs approximately 13 million people, with a shortage of over 1 million material handling jobs. Goldman Sachs expects widespread commercial deployment of humanoid robots to not occur until 2027 to 2029. (Cailian Press)
Meituan open-sourced its trillion-parameter large-scale model LongCat-2.0, and simultaneously released the inference code for domestically developed Chinese card processors.
According to Beating's monitoring, Meituan has officially open-sourced its trillion-parameter large-scale model, LongCat-2.0, with a total of 1.6T parameters and an average activation of approximately 48B, designed specifically for real-world agentic coding tasks. Architecturally, it innovatively introduces LongCat sparse attention and N-gram embedding. The former reduces fragmented memory access through flow-aware indexing and hierarchical indexing, accelerating training and inference with millions of contexts; the latter, while achieving nearly 97% sparsity in MoE, invests 135B parameters into the embedding layer, balancing parameter gains and structural stability. Post-training employs multi-teacher online distillation, categorizing experts into Agent, Inference, and Interaction types, seamlessly integrating them on a domestic computing power cluster through the MOPD architecture. As the industry's first trillion-parameter model to complete inference on a 50,000-card domestic computing power cluster, LongCat-2.0 validates the mature capability of domestic chips to handle complex large-scale model tasks. To address the multiple limitations of domestically produced Chinese chips in terms of memory, bandwidth, and interconnects, Meituan has made breakthroughs in three areas: model, chip adaptation, and deployment. At the model level, ScMoE leverages the core control capabilities of domestically produced chips to achieve physical core-level parallelism for Dense and MoE branches, combined with KV-cache partitioning to alleviate the pressure on ultra-long context memory. At the chip adaptation level, Super Kernel reduces operator startup overhead, and Weight Prefetch hides I/O latency, maximizing hardware utilization under constrained conditions. At the deployment level, PD separation is adopted to balance TTFT and TPOT, along with asynchronous Expert-Parallel load balancing to solve load unevenness under high EP (efficiency level). This open-source release simultaneously provides multiple precision versions, including BF16, FP8, and INT8, and fully opens up inference results optimized for domestic computing power, aiming to enable existing domestically produced cards and even older cards to smoothly deploy trillion-model inference services. --------------------------------- Click the original link below to join the Beating · Lark AI news channel and monitor global AI hot topics and news 24/7.