Where capital flows is where talent concentrates, where production capacity gets built, and where the next commercial technologies will come from.

The China Round is free, published weekly, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

222 filings this week. The single biggest check went to a company that’s already public, and it went into a subsidiary. A robotics professor raised $100 million twice in 33 days. A June government directive may be tying this week’s AI, chip, and robotics capital into one policy-driven stack. And two city governments wrote checks into the same startup’s round, nine weeks after Beijing told them to stop competing. Here’s where the money went.

Where the Money Went

AI 53 | Semis 39 | Adv. Mfg 42 | Robotics 33 | Energy 29 | Frontier 13 | Aero 13

222 deals | 24 deals disclosed a combined $2.04B (~¥14.7B)

AI led the week on deal count (53 of 222 filings), but most of that volume was small and undisclosed. Only 24 of 222 deals disclosed a figure at all. Semiconductors, with only 39 deals, pulled in nearly half the week’s disclosed capital, $973M of the $2.04B total. Almost all of that came from one deal: ESWIN Materials’ ¥6.5 billion (~$903M) capital increase into its Wuhan wafer subsidiary. Robotics saw two standouts: DISCOVER Robotics raised roughly $100 million twice in 33 days, and Konvery brought three robot manufacturers onto its cap table as strategic investors. In AI, Gradence reported the top coding benchmark score, though we couldn’t find the company on the benchmark sites it references. Five quantum computing deals landed this week, all on the Radar. Aerospace stayed state-anchored, with i-Space closing another ¥1 billion (~$139M) tranche of its E round on the way to a STAR Market listing (the Shanghai exchange’s board for high-growth tech companies).

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Spotlight

Gradence (梯度回音)

Angel Round, Undisclosed Amount, Valuation Undisclosed

A multi-agent coding harness running on top of OpenAI’s model claims the top benchmark scores in software engineering.

The China Round is free, published weekly, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure USD AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

The structural stories this week sit further down the cap table. Three competing humanoid robot makers put money into the same AI-model supplier, a cooking-robot company reported turning profitable, and a Chinese cockpit chip appeared inside a Volkswagen Group vehicle for the first time. Moonshot’s $3.5 billion F round dominates the numbers.

Where the Money Went

AI 35 | Semis 28 | Mfg 35 | Energy 21 | Robotics 14 | Frontier 11 | Aero 8

152 deals | $4.18B disclosed | $683M ex-Moonshot

Three fusion companies raised in one week, with CATL leading its first fusion bet into a 7-month-old startup. Robotics capital went beneath the robot. Three rival humanoid makers backed the same AI-model supplier (Delta Intelligence, nearly ¥500M at a ¥3B valuation) while cooking robots and dexterous hands split the remaining $97M in disclosed robotics capital. Semiconductors stayed state-heavy at later stages, anchored by SiEngine’s $100M for the cockpit chip inside a Volkswagen and Angstrom Excellence’s ¥1B for wafer metrology equipment. AI was almost entirely Moonshot’s $3.5B F round; strip it out and the week split between agent infrastructure and biological AI. Corporate strategics led or co-led an unusually large share of headline deals, with CATL in fusion, Alibaba Cloud in AI ops (while running a competing internal product), China Merchants Capital in cooking robots, and Sungrow and Tianqi Lithium putting a combined ¥805M (~$112M) into battery maker Sunwoda EVB.

Spotlight

Delta Intelligence (德塔智能)

Angel Round (6th round), Nearly ¥500M (~$69M), ¥3B (~$417M) valuation

Humanoid robot foundation-model platform, six rounds in six months.

It is free, published weekly, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

A seven-month-old company raised $80M at angel stage, two rival startups in Shanghai raised in the same week for competing visions of AI memory, and AI-generated 3D content produced the category’s largest round to date. Elsewhere, a medical device maker and a landscaping contractor turned up among the investors in an AI chip company that has yet to sell anything. Several deals were timed to coincide with WAIC, where Xi Jinping announced the creation of the World Artificial Intelligence Cooperation Organization (WAICO). The other kind of memory had its own week. As this issue goes out, CXMT (长鑫科技), China’s largest DRAM maker, saw its shares begin trading in Shanghai at ¥49.5 against an ¥8.66 issue price, a 471% jump that briefly made it the most valuable company on the A-share market at over ¥3.3 trillion (~$458B).

Where the Money Went

191 deals this week across AI, robotics, semiconductors, energy, and frontier tech. 22 deals with published exact amounts disclosed a combined $1,469M (~¥10.6B), a strong but not exceptional week by 2026 standards. AI dominated both the deal count and the disclosed capital, and advanced manufacturing spread across the widest range of sub-sectors.

🧠 AI (50 deals)

A cluster of large rounds arrived within days of each other, several timed to coincide with WAIC in Shanghai. Meshy raised ~$400M (~¥2.9B) for AI-generated 3D content, the largest known round in that category globally. FlovaAI, a 7-month-old company founded by the developer of CapCut, raised $80M (~¥576M) at angel stage. Two “AI memory” startups, Red Bear AI and MemTensor, both raised in Shanghai in the same week with competing architectures for persistent AI memory, the ability for language models to remember prior conversations and accumulated knowledge. HiDream.ai (智象未来) pulled in ¥1.5B (~$208M) with China’s Social Security Fund co-leading, a marker of how Beijing categorizes generative AI as strategic infrastructure. Calculet (原粒半导体) raised over ¥700M (~$97M) for AI chips built to run agents on local hardware. Design Order (设序科技) raised its B round for industrial AI software that embeds inside Siemens NX, with plans to enter the European market this year.

🤖 Robotics (33 deals)

The highest-valued robotics round went to Psibot (灵初智能), which raised ~$100M (~¥720M) at a $1.48B valuation with Chery Auto leading and Lens Technology co-investing. A car manufacturer and an Apple/Tesla components supplier are writing the checks for an embodied AI company (AI systems built to control physical robots rather than run as software alone), not traditional VCs. Elsewhere, Xynova (曦诺未来) raised ¥500M (~$69M) for dexterous robot hands, extending a pattern where each of its rounds has been led by a different platform company (CATL, JD, Li Auto, and now Meituan). Yimu Tech (一目科技) hit ¥10B (~$1.39B) valuation on its E round for tactile sensors. Futuring Robot (未来不远机器人) raised ~¥1B (~$139M) at Pre-A for home service robots.

⚡ New Energy & Materials (17 deals)

Mostly undisclosed amounts, with state and corporate capital dominating the cap tables. Xuandian (玄电新材) raised near ¥100M (~$14M) for conductive carbon black, a specialty chemical added to lithium-ion battery electrodes to improve conductivity. TCL’s venture arm led the A round for Tianjiao Xinneng (天交新能), a new energy company. China General Nuclear Power Group (CGN), a state-owned nuclear operator, opened its Yunnan renewable energy subsidiary to outside capital.

🔬 Semiconductors (27 deals)

Mostly undisclosed amounts and mostly state-adjacent capital. Tongyong Semiconductor (通用半导体) disclosed its B round at several hundred million RMB (~$40M+). The rest were smaller or undisclosed rounds across analog chips, micro-sensors, and lithography components. Zhongxin Juyuan (中芯聚源), a fund linked to SMIC, China’s largest chipmaker, appeared in two deals.

💡 Frontier Tech (9 deals)

LiangYi (两仪万象) raised its A+ at ¥2B (~$278M) valuation after setting a world record of 11,000 trapped atoms for neutral-atom quantum computing. Trapped atoms serve as quantum bits (the quantum equivalent of a transistor), so more of them, controlled precisely, means more computing power; LiangYi’s 11,000 nearly doubles the previous record of 6,100, held by Caltech. Lei Jun’s Shunwei Capital has invested in every one of LiangYi’s rounds. Jingjie Juneng (竞界聚能) raised a hundreds-of-millions-of-RMB (~$40M+) angel round at ¥1.5B (~$208M) valuation for a fusion reactor that uses an unconventional approach to confining the superheated plasma that powers the reaction. Jingjie Juneng’s round drew an unusually broad 9-investor syndicate led by Loongson VC, the venture arm of China’s flagship domestic CPU company.

🚀 Aerospace & Defense (8 deals)

Xingchen Daohe (星辰道合) raised a near-¥100M (~$14M) angel round for satellite communications equipment. The remaining seven deals were smaller or undisclosed.

⚙️ Other Advanced Manufacturing (47 deals)

The largest disclosed round went to Lanhe Tech (蓝河科技), which raised a B+ of several hundred million RMB (~$40M+) for UV-LED equipment used to cure coatings and etch circuits in electronics manufacturing. The round was led by the China Internet Investment Fund, a fund under China’s State Council (the country’s top government body). IBDTEC (博顿光电) raised a B+ for ion beam equipment used in manufacturing superconducting tape, a material that carries electricity with zero resistance and is critical for advanced magnets in everything from MRI machines to fusion reactors. The company claims near-100% domestic market share in that niche.

Spotlight

Meshy

B Round, ~$400M (~¥2.9B), ~$1.5B valuation (~¥10B+)

AI 3D content generation platform.

The China Round is a weekly report tracking venture and strategic investment activity across China’s core technology sectors: AI, robotics, semiconductors, new energy and materials, aerospace and defense, and frontier tech.

The China Round is free, published weekly, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

This is quite a few days late. I appreciate your patience. And fret not, there will be two editions this week. I was busy with WAIC and, more importantly, getting married.

The World AI Conference opened in Shanghai this week with Xi Jinping delivering the keynote, calling for open-source AI cooperation and pledging 5,000 AI training places for developing countries over the next five years. Ten days earlier, at a pre-WAIC press conference, the Ministry of Industry and Information Technology gave its most concrete production target yet for humanoid robots: 100,000 units in 2026, more than four times the roughly 24,000 deployed worldwide at the end of 2025.

Where the Money Went

This week, 159 deals landed across seven sectors, and 25 of them disclosed a combined $1.02 billion (~¥7.3 billion). Most deals came without published figures, so the actual capital deployed was considerably higher. AI led in deal count with 40 transactions, followed by semiconductors (28), robotics (25), and other advanced manufacturing (24). Industrial customers, not venture funds, led several of the largest rounds this week, buying equity directly in the suppliers they need.

🧠 AI (40 deals)

The two largest disclosed AI rounds went to on-device models, not cloud-scale foundation models: ModelBest (面壁智能) accumulated over ¥5 billion (~$694 million) across H1 2026 for models that run on phones and cars, and AIsphere (爱诗科技) closed its C+ at ¥2.98 billion (~$414 million) with Alibaba leading. TASHAN (他山科技) closed a B round with industrial customers as investors. At the early stage, seed and angel deals skewed toward embodied intelligence, with multiple rounds backing “world models” (AI systems that simulate physical cause-and-effect so a robot can predict what happens before it acts) and vision-language-action systems (models that turn a spoken instruction directly into physical movement).

⚡ New Energy & Materials (20 deals)

Power, batteries, and the physical infrastructure beneath the AI boom. Marvel-Tech (慕帆动力) closed a Sequoia-led C round for on-site AI datacenter power generation. ENN Fusion (新奥聚变) opened its first external round at ¥10.6 billion after more than a decade of internal R&D. Ganfeng Battery (赣锋锂电) raised twice in three weeks for solid-state batteries. Linkcharging (领充新能源) raised a strategic C round with multiple automakers. Generating, storing, and delivering power is becoming its own investment category, driven by AI compute demand.

🔬 Semiconductors (28 deals)

State-capital coalitions and strategic investors dominated. Liuyuewei (六岳微) raised ¥500 million in a Series A for domestically developed digital signal processors (the chips that convert real-world signals like sound and radar into digital data), backed by a Guangdong government coalition. Cygnusemi (星思半导体) completed its third round of 2026 for satellite baseband chips (the component in a phone or terminal that decodes wireless signals), reaching ¥12 billion. Shuoguang Precision (烁光精密) attracted two listed-company strategic stakes within weeks for co-packaged optics components, the light-based interconnects replacing copper inside AI data centers. Multiple deals showed listed companies taking direct equity in their own suppliers rather than routing through venture funds.

🤖 Robotics (25 deals)

Capital came from unusual directions. LimX Dynamics (逐际动力) raised $200 million in a Pre-IPO, over 70% from overseas investors. CATL took RoboParty’s (萝博派对) entire Pre-A alone. Shanghai Electric led DexRobot’s (灵巧智能) Series A and co-founded two manufacturing joint ventures with the company. Seven of 25 deals were at the angel stage, suggesting a new wave of company formation. Industrial companies are buying equity in their future robot suppliers, locking in components before the production ramp.

💡 Frontier Tech (11 deals)

The largest round came from one of the oldest companies: Wentian Quantum (问天量子) raised ¥600 million in a Series B after 17 years in quantum communication. Bama (八匹马) raised over ¥100 million for superconducting magnets (magnets cooled to near absolute zero to generate extremely strong magnetic fields) and cryogenics serving quantum computing, fusion, and semiconductor fabrication. Shuyanjuchuang (束研聚创) raised ¥100 million at the angel stage for neutral beam injection systems (equipment that shoots high-energy particles into a fusion reactor’s plasma to heat it enough to sustain a reaction). Two of three deals are component suppliers to other frontier sectors, a sign that the infrastructure layer beneath quantum and fusion is now investable on its own.

🚀 Aerospace & Defense (11 deals)

LegendSpace (临界航天), a six-month-old startup, raised ¥200 million (~$28 million) at the angel stage for AI-accelerated liquid rocket engine development. Galactic Energy (星河动力), China’s most-launched pre-IPO commercial rocket company with 21 flights and 89 satellites delivered to orbit, took an investment from GAC Capital, Guangzhou Automobile Group’s corporate venture arm. GAC Group launched its own flying car brand earlier this year and has backed autonomous driving companies including Momenta and Pony.ai, a portfolio that puts rocket launches closer to the core business than it first appears.

⚙️ Other Adv. Manufacturing (24 deals)

Hardware teams leaving big companies to build consumer products for export. Deeplore (蓝洞探索), three former DJI engineers, raised a seed for an AI diving mask. LightMake (轻量智造), a former AnkerMake lead, raised an angel for 3D printers targeting North America and Europe. Whale (帷幄) raised $40 million from Hyundai and Japanese bank corporate venture arms, bringing its total Series C to over $100 million, more than half its revenue now international. Chinese hardware expertise built at scale inside large companies is spinning out and shipping directly to Western customers.

Spotlight

Deeplore (蓝洞探索)

Seed, Tens of millions of RMB (several million USD), Val. ¥150M (~$21M)

AI diving mask with a heads-up display and real-time marine species recognition.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Happy Friday. China’s first unified outbound investment regulation took effect on July 1, restricting how technology can leave the country. The same week, 141 deals closed across seven sectors. More on those rules below.

Where the Money Went

141 deals across seven sectors. 24 disclosed exact amounts, totaling $2.2 billion (~¥15.6B), with most of the capital concentrated in a satellite mega-round and several hundred-million-dollar AI raises.

🧠 AI (26 deals)

Shengshu Technology (生数科技) closed a $500 million (~¥3.6B) B+ round for Vidu, its AI video platform. Tripo AI raised $150 million (~¥1.08B) in an A+ round for AI-generated 3D assets, its third raise in four months. DeepCtrls (深度智控) pulled in hundreds of millions of RMB with Jinko Solar as a strategic investor (covered below). MindRank (德睿智药) raised $52 million (~¥374M) for AI drug discovery, with its lead candidate now in Phase III (covered below). Below the growth rounds, a cluster of Pudong-backed seed and angel deals continued Shanghai’s pattern of systematic early-stage deployment.

⚡ New Energy & Materials (23 deals)

Starchens (星辰新能) led the sector with a ¥500 million (~$69M) B round backed by CITIC Securities Capital, ICBC Capital, and East Money, a lineup of securities and bank-affiliated investors more typical of pre-IPO rounds. The rest split between battery materials, hydrogen, energy storage, and specialty chemicals, with state-linked capital from Hefei, Nanjing, and Jiangsu backing early- and growth-stage rounds.

🔬 Semiconductors (22 deals)

Twenty-two deals, nearly all with undisclosed amounts. Sicreat (新美光) closed a ¥1 billion (~$139M) C+ round for CMP (chemical-mechanical planarization) polishing pads, a key semiconductor consumable (more below). EDA (chip design software), chiplet packaging, and optoelectronic chips each drew a handful of deals. Several semiconductor materials companies are raising in Suzhou, continuing that city’s emergence as a vertically integrated chip-materials cluster.

🤖 Robotics (18 deals)

RobotEra (星动纪元) closed a ¥1 billion (~$139M) B round led by Chengtong, a fund under SASAC (China’s state-asset regulator), part of ¥2.5 billion (~$347M) raised across three rounds in roughly 60 days. Morphi (墨奇智能) pulled in hundreds of millions of RMB in what is reportedly one of the largest disclosed angel rounds in China’s embodied-AI sector (AI designed to operate physical hardware like robots), with Alibaba and Tencent co-anchoring for a six-month-old company. Motorevo (泉智博) completed its seventh round in 18 months for humanoid robot joint modules.

💡 Frontier Tech (8 deals)

Two brain-computer interface companies raised in the same week: Gestala (格式塔科技), a non-invasive ultrasound BCI startup, closed a ¥442 million (~$61M) angel+ round (covered below), while NeuroXess (脑虎科技) raised an A+ round as it began Class III clinical trials at Huashan Hospital. QBoson (玻色量子) closed a Pre-IPO round and filed for IPO coaching (the formal process of engaging an underwriter to prepare a company for listing) three days later. SynMetabio (贻如生物), a synthetic biology company making cultivated leather for luxury brands, closed its A round with Ordos Group co-leading (covered below).

🚀 Aerospace & Defense (16 deals)

Changguang Satellite (长光卫星) dominated with a ¥5 billion (~$694M) strategic round, the largest single raise in the sector this week. The company operates 161 satellites, the world’s largest sub-meter-resolution commercial remote-sensing constellation. Space Pioneer (天兵科技) added ¥200 million (~$28M) in strategic capital. Kaipu Dynamics (开普动能), an eVTOL (electric vertical takeoff and landing) electric propulsion startup founded by a former Rolls-Royce division director, raised an angel round (covered below). Most of the remaining deals were seed and angel rounds for early-stage space-tech and low-altitude economy startups, including Ruiqi Deep Space (瑞启深空), a four-month-old constellation startup that raised ¥220 million (~$31M) at a ¥1.1 billion (~$153M) valuation from Suzhou state funds.

⚙️ Other Adv. Manufacturing (28 deals)

Snapmaker (快造科技) raised ¥1 billion (~$139M) in a C round for consumer 3D printing (covered below). CLAWLAB (浪爪智能) raised hundreds of millions of RMB with miHoYo leading (covered below). Thinkhead (上海星合), a 17-year-old bootstrapped machine-tool manufacturer, took its first outside capital. Coffee robot maker InSpace/XBOT (影智科技) closed a B round. The rest spanned optics, precision measurement, industrial equipment, and microfluidics (tiny channels etched into chips to manipulate fluids for medical diagnostics and lab work).

Spotlight

Gestala (格式塔科技)

Angel+, ¥442M (~$61M), Valued at ¥4.2B (~$583M)

Non-invasive ultrasound brain-computer interface.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Happy Friday everyone. Let’s get straight into it.

Where the Money Went

163 deals across seven sectors. 37 disclosed exact amounts, totaling $5.9 billion (~¥42.4B). Strip out Kling AI’s $3 billion debut raise and the remaining 36 deals still disclosed $2.9 billion (~¥20.8B). Robotics led on volume (37 deals).

🧠 AI (35 deals)

Kling AI’s $3 billion first external raise dominated the sector and the week (covered below). Several ¥1 billion+ growth rounds closed, including DexForce Technology and Tripo AI (both in Radar below), and Xellar Biosystems (耀速科技), whose organ-on-chip platform screens drug candidates on chip-based organ models (covered below). At the other end, a cluster of seed and angel rounds backed brand-new entrants. Klaren Intelligence (厘清智能), a startup building world models, raised several hundred million RMB with HongShan (红杉), Hillhouse, and Shunwei all on the cap table for a seed round. Founded in April 2026. Eighteen AI companies raised at valuations of ¥100 million (~$14M) or less.

⚡ New Energy & Materials (17 deals)

Mostly sub-¥100 million (~$14M) rounds across battery materials, energy storage, and specialty chemicals. Yingong Technology (隐功科技) raised ¥100 million (~$14M) in a Pre-A for nanocomposite materials, and Anputai (安普态) closed a near-¥100 million A round in advanced insulation, both backed by state-linked funds.

🔬 Semiconductors (31 deals)

31 deals, led by Gowin Semiconductor’s Pre-IPO (covered below). EDA, chiplet packaging, and MEMS sensors each drew 1 to 3 deals, alongside camera sensor chips and power management ICs. Qili Semiconductor (齐力半导体) raised ¥100 million (~$14M) for chiplet packaging at Zhangjiang, and Jiyi Semiconductor (集溢半导体) raised ¥130 million (~$18M) for analog chip design. State capital appeared in investor lists across the sector, with Guangdong, Jiangsu, and Zhejiang government funds all active.

🤖 Robotics (37 deals)

The most active sector by deal count, with three mega-deals (AI2 Robotics, X Square Robot, and Boundless Motion, all covered in Radar below). Below those, the deals split between platform-backed humanoid companies and smaller startups building components, sensors, or manipulation software. Fifteen deals closed at valuations of ¥100 million (~$14M) or less.

💡 Frontier Tech (11 deals)

Eleven deals. SpinQ (量旋科技) raised ¥1 billion (~$139M) in a D-round for quantum computing (more in Radar below). Xinghe Fusion’s (星核聚变) ¥833 million (~$116M) debut was the largest first-round raise in Chinese private fusion, backed by 25 investors including SAIC Motor. Two other fusion companies also raised this week, Andong Jubian (安东聚变) and Chaoci Xinneng (超磁新能), making it a three-fusion-deal week. SynSense (时识科技) closed several hundred million RMB for neuromorphic chips, event-driven processors that react only to changes in a scene rather than analyzing every frame, cutting power consumption for always-on cameras and sensors.

🚀 Aerospace & Defense (8 deals)

Eight deals, dominated by Hongqing Technology’s ¥1.3 billion (~$181M) Pre-B for its satellite constellation (covered below). Puxing Aerospace (谱星航天) raised several hundred million RMB across combined rounds for optical remote-sensing payloads, with plans for a 1,024-satellite constellation.

⚙️ Other Adv. Manufacturing (24 deals)

24 deals spanning optoelectronics, industrial equipment, and consumer hardware. Sinoscience Fullcryo’s ¥1 billion (~$139M) Pre-IPO for cryogenic equipment (covered below) was the sector’s largest. CAYE raised ~¥400 million (~$56M) in a B-round for coffee machines (covered below). At the other end, AIVELA raised several million dollars for its smart ring.

Spotlight

Kling AI (可灵AI)

First External Round, $3B (~¥21.6B), Valued at ~$18B (~¥129.6B)

Kuaishou’s video generation platform raised its first outside capital, with $500M in annualized revenue and a Hong Kong IPO planned within 12 months.

A quarter of Xinjiang’s annual generation is exported east across transmission lines, capturing generation revenue but little else for the province. Much of the renewable surplus beyond that is curtailed: the transmission lines are at capacity and local demand is too low to absorb it.

Renewables account for over three-quarters of Xinjiang’s installed power capacity but only a quarter of its actual generation: wind and solar produce intermittently, and when they do, there is often nowhere for the power to go. Of what is exported east, less than a third is green.

A policy framework introduced in China’s 2026 government work report proposes capturing some of that surplus by converting electricity into AI compute. The framework is called 算电协同 (”compute-power coordination”) and Xinjiang is the first pilot region.

If all goes to plan, Xinjiang aims to reach 60 exaflops of compute capacity by the end of this year, with construction underway across four cities.

AI’s power problem

For most of the past few years, AI infrastructure headlines centered on chip supply, but that constraint is easing. Nvidia has scaled production, hyperscalers are deploying custom silicon, and China’s Huawei shipped the Ascend 950PR in Q1 2026 with roughly 2.8x the inference throughput of Nvidia’s H20 and its own domestically produced HBM. Government mandates require at least 80% domestic AI chips across the planned data center buildout.

Memory remains tight globally: SK Hynix and Samsung still control over 95% of HBM supply outside China, and Chinese memory maker CXMT’s placement on the Pentagon’s 1260H list has complicated supply chains enough that Apple is lobbying the White House for guarantees it can continue sourcing from the company. But the harder constraint is power.

In the US, new grid connections can take years. At the World Economic Forum in Davos in January, Elon Musk warned that the industry would soon be “producing more chips than we can turn on.” He put it bluntly: “The limiting factor for AI deployment is fundamentally electrical power.” He added: “except for China.”

In the US, over 2,000 GW of generation and storage capacity is waiting to connect to the grid. The median project that reached commercial operation in 2025 spent over five years in the queue. The International Energy Agency estimates that around 20% of planned data center projects could be at risk of delays. FERC responded in June with orders to fast-track data center grid connections, but new facilities may still need to bring their own power or pay for grid upgrades.

Pent-up energy

China generates more than twice as much electricity as the United States. BloombergNEF projects it will add almost six times US electricity generation capacity over the next five years. A lot of that will be renewables. In 2025 alone, China increased wind and solar capacity by over 430 GW, more than half of all global renewables additions that year.

Much of this capacity is concentrated in western provinces, where land is vast, populations are sparse, and wind and solar resources are among the strongest in the country. Xinjiang’s geography makes the case: 1.66 million square kilometres of mostly arid basin and steppe, flanked by the Tianshan mountains, with some of China’s highest solar irradiance and wind corridors like Dabancheng that rank among the country’s best. There is plenty of room for turbines and panels, and plenty of wind and sun to power them. But local demand is thin.

Xinjiang crossed 100 GW of wind and solar installed capacity at the end of 2024, a first for Northwest China. Including hydro and other renewables, total clean energy capacity reached 173 GW within a total grid capacity of 219 GW by mid-2025. But the province’s ability to use all that power locally has lagged behind its ability to generate it. Conditions have improved from historical lows, but not enough: as of early 2025, only 67.6% of available renewable generation was actually used, meaning a third still went to waste.

The traditional solution has been to export the surplus east via ultra-high-voltage DC transmission lines: Hami-Zhengzhou (commissioned 2014), Changji-Guquan (2019, at 3,293 km and 12 GW capacity the world’s longest), and Hami-Chongqing (2025). Changji-Guquan alone has delivered 84 billion kWh of green electricity since commissioning, all consumed at the far end in Anhui.

At projected 2026 curtailment rates, Xinjiang’s renewable fleet will leave untapped the equivalent of more than eight times the annual electricity consumption of Elon Musk’s xAI Colossus supercomputer.

Building compute where the power is

China’s first attempt to build compute in the west was 东数西算 (”East Data, West Compute”), launched in 2022. The program designated 8 national compute hub nodes, including Inner Mongolia, Guizhou, Gansu, and Ningxia, and built real infrastructure: 633 hyperscale and large data centers delivering 268 exaflops of national computing power by 2024.

The program built real capacity, but utilization lagged. The Oxford Institute for Energy Studies found energy savings of 4 to 12% from moving data centers west, though western centers often lacked the fiber infrastructure to serve eastern clients in real time, and the companies, talent, and customers remained concentrated on the coast. Western data center utilization rates settled at 20-30%. Over 100 data center projects have been scrapped nationally in the last 18 months, and the government imposed a moratorium on new large-scale facilities in cities where existing centers operate below 50% utilization.

Compute-power coordination, the successor framework, takes a more focused approach. Rather than trying to solve those demand-side problems directly, it asks whether energy economics alone can pull enough latency-tolerant AI workloads west. It bypasses the moratorium by granting energy-rich provinces the same policy benefits as the original 8 hub nodes based on their power resources, not administrative designation. All new data centers in hub regions must source at least 80% of their electricity from renewables, a target western provinces already meet by default.

Xinjiang, which was not one of the original 8 nodes, was granted the same pilot status. It then launched what its authorities describe as China’s first multi-user 绿电直连 (”green electricity direct connection”) pricing, bypassing the traditional grid to connect power generation directly to the data center at 0.31 yuan per kWh (~$0.045/kWh). That is 0.04 to 0.07 yuan below the standard grid-delivered tariff and cheaper than Inner Mongolia’s 0.35 yuan per kWh (~$0.051/kWh), which Xinhua describes as one of the lowest among the national data center clusters.

Despite frequent claims that China has an energy cost advantage over the West, the Oxford study found that China’s industrial electricity prices are broadly comparable to those in the US. A data center in Guangdong or Jiangsu faces delivered costs of RMB 0.60-0.75 per kWh (~$0.08-0.14/kWh), near or above industrial rates in Virginia, the largest US data center market, because coastal Chinese provinces layer grid charges, capacity fees, and cross-subsidy surcharges on top of generation costs. Western green direct connection pricing at 0.31 yuan is roughly half the eastern rate, which is the real incentive for moving workloads west.

In April 2026, four central agencies led by the National Energy Administration jointly published a 29-item action plan targeting a “safe, green, economical energy guarantee system” by 2027 and “world-leading” clean energy supply for AI compute by 2030. The plan calls for million-kW-scale AI compute facilities with coordinated energy systems, multi-year green power contracts, and infrastructure REITs as a financing vehicle for compute facilities.

The NDRC is drafting a plan to spend 2 trillion yuan (~$295 billion) over 5 years on a nationwide AI data center grid, funded by sovereign debt and ultra-long special government bonds, with China Mobile and China Telecom as primary operators. The total could exceed 5 trillion yuan (~$740 billion) if power grid upgrades are included. Compute-power coordination is one of the frameworks that determines how energy-rich provinces participate in this nationwide buildout.

The demand wave

The infrastructure is being built to meet a compute demand curve that is still steepening. Deloitte estimates that global demand for AI compute is rising four to five times per year through 2030, driven primarily by inference rather than training. Inference workloads now account for roughly two-thirds of all AI compute, up from a third in 2023 and half in 2025. The market for inference-optimized chips alone is projected to exceed $50 billion in 2026. In China, computing-related electricity consumption rose from 82.4 billion kWh in 2019 to 196 billion kWh in 2025. The China Academy of Information and Communications Technology projects it could reach 500 to 700 billion kWh by 2030, up to 5.3% of total national demand.

China’s domestic AI ecosystem is generating much of that demand. Chinese platforms processed 140 trillion tokens per day in Q1 2026, a more than 1,000-fold increase from 100 billion per day in early 2024. Chinese open-source models surged from 1.2% of global usage in late 2024 to nearly 30% by mid-2025, and by June 2026 accounted for roughly 48% of token usage on OpenRouter, overtaking US models, with DeepSeek, Qwen, and Zhipu’s GLM leading the expansion.

Goldman Sachs estimates that China’s top internet firms will invest over $70 billion in data center capital expenditure in 2026, and reports that Chinese data center power demand rose 25% in 2025.

The growing dominance of inference might seem to work against Xinjiang’s case, since inference typically runs close to the end user. But much of the fastest-growing inference demand is not real-time. User-facing inference (search, voice assistants) needs to run close to the user and will stay in eastern cities. Training is less latency-sensitive but faces its own constraint: as one executive told Caixin, the datasets are so large that “companies sometimes have to physically transport hard drives” rather than transmit them east to west. Planned network infrastructure investment aims to close that bandwidth gap. But once the data arrives, training runs are exactly the kind of sustained, power-hungry workload that suits cheap western electricity. The same is true of batch processing, agent workflows, and offline industrial analytics, and these workloads are growing fastest. In January 2026, eight ministries set a target of 1,000 industrial AI agents deployed across manufacturing, logistics, and public services by 2027. Some of these, like real-time robotics control, need to run locally. But many, like logistics optimization, demand forecasting, and document processing, are batch workloads that need cheap, reliable power and a network connection, not proximity to the end user. That is the market compute-power coordination is designed to serve.

The funding landscape

In April 2025, China launched a ¥60 billion (~$8.3 billion) state-backed AI fund to invest across the full AI industrial chain, with its first-year focus on semiconductors and computing infrastructure. ByteDance’s 2026 capital expenditure alone is ¥160 billion, over half of it on AI chips. Alibaba has committed ¥380 billion over three years to cloud and AI hardware infrastructure.

Below the hyperscalers, venture capital is filling the infrastructure stack. Some notable raises this year across the energy and cooling layers of AI compute:

Qingqi Power (清启动力): micro gas turbines for distributed data center power. Pre-A round, nearly ¥100 million (~$14 million), ¥500 million valuation. Facilities that cannot wait on the grid use on-site turbines to generate power where the connection has not yet arrived.

Xinhan Intelligence (芯寒智能): cooling systems for AI compute clusters. Pre-A round, hundreds of millions of yuan, ¥1.5 billion valuation. AI accelerators run hot and pack tightly, and at cluster scale the heat load outstrips what air cooling can handle. Cooling also sets PUE, the main lever on a facility’s operating cost.

Afalight (埃尔法光电): co-packaged optics. D round (sixth total), ~¥100 million, ¥1.2 billion valuation. Supplies a 2.4 Tbps optical engine to Alibaba’s AI data centers. As clusters scale, the copper links between racks and the network become the bottleneck on data movement, and co-packaged optics moves the transceiver onto the switch package to push interconnect bandwidth past that limit.

MetaPWR (沛塬电子): power modules for AI compute. Strategic round, undisclosed amount, ¥500 million valuation. AI racks pull very high current at low voltage, and the rack’s power conversion stage has to deliver that cleanly and reliably. Generic modules are not rated for the load profile.

Four cities, one value chain

Four cities are dividing the work: Karamay runs the most efficient facilities, Changji is building new capacity with major tech partners, Hami dispatches compute to Chongqing, and Urumqi connects westward to Central Asia.

1. Karamay (克拉玛依) has some of the most energy-efficient data center infrastructure in China. Carbon and Network Tech runs facilities with a PUE under 1.1 (PUE measures how much energy goes to compute vs. cooling and overhead; a perfect score is 1.0, and typical facilities run 1.3-1.5), with cooling and overhead energy one-fifth that of a conventional data center thanks to liquid cooling and Xinjiang’s cold, dry climate. The company has used 100% green power via green electricity certificates since 2024 and was listed on the 2025 National Green Compute Facilities roster. Karamay dispatches compute to Shanghai under a cross-regional framework.

2. Changji (昌吉) broke ground in May 2026 on a green direct-connect photovoltaic project paired with a China Unicom 16,000P intelligent compute infrastructure build at the Xinjiang Information Industry Park. Alibaba, ByteDance, and Zhipu have all reached cooperation agreements, with scheduled completion in November 2026.

3. Hami (哈密) has been designated by the National Data Bureau as an implementation city for both the Xinjiang-to-Chongqing compute corridor and compute-power coordination. A dedicated all-optical network link delivers under 20 ms one-way latency to Chongqing across 4,000 km, with 20,000P of compute already operational and a target of 40,000P by year-end.

4. Urumqi (乌鲁木齐) is building a national-level internet backbone direct connection point alongside a BRICS digital industry cooperation network city node, positioning itself as a compute hub serving Central Asia and Europe. Xinjiang borders Kazakhstan, Kyrgyzstan, Tajikistan, Pakistan, and Mongolia, and has more than 20 cross-border international fiber cables connecting to those neighbors, recently upgraded to 1.2 terabits (China-Kazakhstan) and 800 gigabits (China-Pakistan). The provincial government describes its cross-border compute services as “算力出海” (”compute going overseas”). So far, the only confirmed services crossing these borders are satellite remote sensing and smart agriculture from Xinjiang’s Space-Air-Ground Integration Lab. The fiber infrastructure exists; commercial AI compute demand from Central Asian markets has yet to materialize. Eight intelligent compute center projects are under construction, and companies including Beijing Wanjie Data and Hefei-based Leinao have established operations. The Xinjiang Daily describes Leinao’s facility here as the first compute center using domestically produced chips. Leinao’s Bitahub platform aggregates self-built and external compute resources and reports a utilization rate above 90%, but that is a platform-level figure, the result of a marketplace that resells compute across multiple facilities. Facility-level utilization in western hubs remains at 20-30%. Whether a platform model can close that gap at scale beyond a single marketplace is untested.

Electricity to compute to tokens

Jin Qian, president of Carbon and Network Tech in Karamay, told the Xinjiang Daily: “Xinjiang is thinking about how to convert electricity into compute, compute into tokens, and serve the world via the internet.”

China does not need to export chips, models, or hardware to serve AI demand beyond its borders. It can deliver tokens over fiber, keeping the infrastructure, energy, and jobs domestic. Each step retains more value locally than the last: raw electricity captures generation revenue, compute adds infrastructure and operations, tokens add the service layer. Geopolitical and data-sovereignty constraints will shape which markets those tokens can realistically reach, but the economic logic of the conversion chain holds regardless.

The electricity-to-tokens framing has taken hold in other compute hubs too. Inner Mongolia’s Ulanqab, just over 200 km from Beijing with 4.2 ms fiber latency, has branded itself China’s “Token之都” (Token Capital) under a three-year action plan (2026-2028), with over 5 million standard server racks signed and 165,000P of running compute. But Ulanqab’s success leans on proximity to Beijing. Xinjiang’s pitch is different: the cheapest green power in the country, direct-connect pricing that undercuts even Inner Mongolia, and cross-border fiber to Central Asia that no eastern hub can match.

What has to go right

SMIC’s co-CEO Zhao Haijun warned on the company’s Q4 earnings call that rushed AI data center capacity could sit idle, describing the pace as “10 years of capacity crammed into two.”

Caixin, citing expert sources, describes compute-power coordination as being in an “early exploration period,” and draws a technical distinction between 电量 (”electricity volume”), the total energy available, and 电力 (”electrical power”), managing instantaneous demand. Xinjiang has plenty of 电量, but the real challenge is 电力. AI training clusters draw power in sharp, irregular spikes that solar and wind cannot match on demand. The green direct connection model that bypasses the grid also bypasses this buffer, so facilities need either substantial battery storage or a robust grid fallback. Some are already building this: a State Power Investment Corporation facility in Xinjiang operates entirely off-grid with on-site solar, wind, and battery storage, and CATL committed over $1.5 billion to data center energy infrastructure in two months, including $577 million into data center power supplier Zhongheng Electric in April and up to $942 million into data center operator VNET Group in May.

Data centers still account for only 1.68% of China’s total electricity consumption, projected to reach 3% by 2030, a narrower scope than CAICT’s broader “computing-related” estimate of up to 5.3%, which includes telecom and edge infrastructure. Compute-power coordination will not solve the curtailment problem in volume terms. The case rests on value density: a kilowatt-hour converted into AI tokens captures far more economic value than one exported as raw electricity, even if the total kilowatt-hours consumed remain a sliver of the surplus.

The timeline mismatch compounds the challenge: large computing centers can be built in 8 to 24 months, but traditional power substations require 3 to 5 years for planning, approval, and construction. Green direct connection lets data centers start operating before the substation arrives, but the grid fallback they will eventually need still takes 3 to 5 years to build.

The Xinjiang Daily itself acknowledges the challenges: “算力基础设施投资大、回报周期长” (”compute infrastructure investment is large, payback period is long”), along with the need for better cross-regional networks and talent.

Conclusion

The question this framework has to answer is the same one East Data, West Compute could not: whether workloads will actually move. Compute-power coordination addresses the cost side of that equation with 0.31 yuan/kWh green direct-connect pricing and equivalent hub-node status. What it does not address is the commercial gravity of the eastern seaboard, the dense concentration of developers, customers, and corporate headquarters that resisted the first wave of westward migration.

If the framework succeeds, it establishes a model with implications well beyond Xinjiang: that energy-rich, compute-poor regions can compete for AI workloads on electricity price rather than proximity, provided they target latency-tolerant workloads, whether training or batch inference, rather than real-time services. That would reframe western China’s renewable surplus as upstream infrastructure for a national or even global AI services layer. The energy still reaches demand, but as tokens over fiber rather than electrons over high-voltage lines, and the bottleneck shifts from the rigid capacity of a transmission corridor to the elasticity of a network. At the token layer, remoteness stops being the obstacle and becomes the advantage: stranded power converted into tokens, carried over fiber to markets the grid was never built to reach.

Where capital flows is where talent concentrates, where production capacity gets built, and where the next commercial technologies will come from.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

This week, a robotics company founded in 2015 with over ¥1 billion (~$139M) in annual revenue filed for its Hong Kong IPO at a ¥19.5 billion (~$2.7B) valuation. The same week, a robotics company founded 90 days ago with zero product raised at a ¥9 billion (~$1.25B) valuation. Both are rational bets. 127 deals spanned every sector, early-stage rounds continued to swell to growth-stage sizes, and the most interesting capital flows crossed sector boundaries.

Where the Money Went

127 deals this week, 49 of which disclosed amounts totaling approximately $1.75 billion (~¥12.6B). Strip out COOWA’s $600 million (~¥4.3B) IPO round and Tongwei Solar’s ¥5.06 billion (~$703M) restructuring, and 47 deals disclosed a combined ~$442 million. Most Chinese deals don’t disclose amounts, so the actual total is higher.

Stage distribution: 42 angel, seed, and pre-A rounds, 49 at Series A/A+, 15 at Series B or later, and 21 strategic investments. The early-stage dominance reflects a market where the embodied AI and physical AI boom is still generating new companies faster than it is graduating existing ones.

🧠 AI (25 deals)

The largest AI cluster spans physical AI infrastructure, video generation, and 3D content. Lightwheel AI (光轮智能) raised ¥1 billion (~$139M) for robot simulation data from a syndicate that includes three listed gaming companies. Sand AI raised over $100 million for video generation that competes with OpenAI’s Sora. Deemos (影眸科技) raised hundreds of millions of RMB for 3D generative AI with clients including Unity, Figma, and Canva. Jiangxing AI (江行智能) closed its third fundraise of 2026, backed by CATL-affiliated capital, Jinkosolar, and Yanzhou Energy as customer-investors.

⚡ New Energy & Materials (16 deals)

The headline is Tongwei Solar’s ¥5.06 billion (~$703M) restructuring, which dwarfs everything else. Beyond that, the energy transition stories are more interesting than the numbers suggest. HYDOtech (海德氢能) attracted a repeat investment from Saudi Aramco’s venture arm alongside Conch Group’s private equity arm, one of China’s largest cement producers. HYLICreate (合源锂创) landed a Xiaomi fund-led round for solid-state batteries with a live factory. Solide (索理德) raised for silicon-carbon anode materials at volume production scale.

🔬 Semiconductors (26 deals)

The second-largest sector by deal count spans optical interconnect chips, AI inference silicon, and specialized sensors. Aluksen Technology (傲科光电子) closed a B++ for high-speed optical chips that connect GPUs inside AI data centers. AIPhotonix (慧芯激光) raised to build its own manufacturing line for gallium arsenide and indium phosphide optical chips, targeting the same AI data center interconnect market. Transtreams (凌川科技) closed an A+ for a video compression chip that outperforms NVIDIA on compression efficiency benchmarks. Juxin Semiconductor (聚芯半导体) filed for a Hong Kong IPO as the world’s fourth-largest optical sensor company by revenue.

🤖 Robotics (20 deals)

COOWA (酷哇科技) is raising $600 million (~¥4.3B) ahead of a Hong Kong IPO at a ¥19.5 billion (~$2.7B) valuation, with SoftBank China Venture Capital backing. At the other extreme, Kunlun Xing (昆仑行机器人) raised an undisclosed amount at a ¥9 billion (~$1.25B) valuation 90 days after founding, with zero product. AGILINK (临界点) hit unicorn status at ¥10 billion in its B round, five months after founding, though unlike most instant unicorns it actually has revenue and 8,000+ dexterous robot hands shipped.

💡 Frontier Tech (4 deals)

The smallest sector by count but one deal carries outsized signal: Juhe Jubian (聚合聚变), a fusion energy startup in Hefei, raised an angel round co-led by Hillhouse Ventures and Sequoia China, the third fusion deal in three consecutive weeks across three distinct fusion approaches.

🚀 Aerospace & Defense (8 deals)

Argo Space Technology (吉天星舟) raised a B round as a profitable space-tech component supplier with 55 payloads delivered and 30 in orbit at a 100% success rate. Jitai Aviation (吉太航空) raised for a modular electric vertical takeoff and landing aircraft, an air taxi that takes off like a helicopter but runs on electric motors, targeting China’s government-designated “low-altitude economy” covering commercial airspace below 1,000 meters.

⚙️ Other Advanced Manufacturing (28 deals)

The largest sector by deal count spans industrial automation, optoelectronics, and specialized manufacturing. Highlights include Fubusi (辅布司), an AI textile cutting company, and Botler Robotics (博特勒), building high-temperature superconducting magnets for fusion reactors.

Spotlight

COOWA (酷哇科技)

Latest round, $600M (~¥4.3B), ¥19.5B (~$2.7B) valuation

Autonomous urban robots that actually make money.

Where capital flows is where talent concentrates, where production capacity gets built, and where the next commercial technologies will come from.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

This past week, DeepSeek raised over $7 billion (~¥51B) in its first-ever external funding round, the largest single financing event in Chinese AI history. The rest of the data is just as revealing: 93 deals in total, a wave of new company formations in physical AI, and at least six companies raising in the same week to build “world models,” AI systems that predict physical cause and effect so robots can plan actions before executing them.

Where the Money Went

Ninety-three deals landed between June 12 and 18. Nineteen disclosed amounts, combining for $8.7 billion (~¥62.6B) in total disclosed capital. DeepSeek alone accounts for 82% of that figure. Strip it out and 18 deals still disclosed a combined $1.6 billion (~¥11.5B), a strong week by any measure.

Roughly 43% of deals were angel or seed rounds, well above the typical weekly mix. This skew reflects a physical AI company-formation wave, with new teams spinning out of established labs and raising within weeks of incorporation.

🧠 AI (24 deals)

AI dominated both deal count and capital. DeepSeek’s ¥51 billion (~$7B+) A round accounted for the vast majority of that capital, but the sector had depth beyond it: LiblibAI raised $300 million (~¥2.2B) for its AI creative platform, SiliconFlow closed a ¥2 billion (~$278M) B round for inference infrastructure, and 卜拉格科技 raised ~$220 million (~¥1.6B) in its first institutional round with no shipped product. A cluster of companies raised to build “world models” for robotics. Physis, Manifold AI, and Synapx all closed world model rounds in the same window. More on this pattern in The Bigger Picture.

🤖 Robotics (13 deals)

Thirteen robotics deals disclosed $278 million (~¥2B). SEAHI Robotics pulled in ¥1 billion (~$139M) for its marine robots, while GigaAI closed a ¥1 billion (~$139M) B2 round for its humanoid platform. ACE Robotics, which builds AI software brains for robots, raised nearly $100 million (~¥720M) at angel stage with a ¥2.6 billion (~$361M) valuation. NOITOM Robotics, a leading player in the global professional motion capture market, raised several hundred million RMB (~$30-130M) for its pivot into robot training data. At the smaller end, a half-dozen angel-stage robotics companies each raised single-digit millions.

🚀 Aerospace & Defense (8 deals)

Eight deals, $264 million (~¥1.9B) disclosed. Emposat (航天驭星) led with a ¥1.4 billion (~$195M) D+ round for satellite ground operations ahead of an IPO filing. ZEROG (零重力飞机工业), which makes both conventional electric fixed-wing aircraft (already shipping, over 1,000 letters of intent) and electric aircraft designed for vertical takeoff and landing (in development), closed a ¥500 million (~$70M) B round led by three Hefei government funds. Juneng Tianqing (聚能天擎) raised several hundred million RMB (~$30-130M) for methane rocket engines at angel stage.

💡 Frontier Tech (6 deals)

Six deals, $125 million (~¥900M) disclosed. Taiyi Quantum (太一量生) raised ¥300 million (~$42M) at Pre-A for its neutral-atom quantum computer, which uses ytterbium atoms suspended in a laser trap rather than the superconducting qubits favored by IBM and Google. The approach runs at room temperature and makes fewer calculation errors, the main bottleneck in current quantum systems. Xeonova (星能玄光) closed a ¥500 million (~$70M) A round for commercial nuclear fusion. Nuclear fusion, the reaction that powers stars, would produce nearly unlimited clean energy if it can be sustained cheaply. Most approaches require enormous reactor chambers costing billions; Xeonova uses a compact alternative reactor design that reaches initial plasma ignition at far lower cost.

🔬 Semiconductors (6 deals)

Six semiconductor deals, mostly with undisclosed amounts. The most notable chip deal of the week was NanoCore Chip (微纳核芯), which raised ¥1 billion (~$139M) in a B+ round for its RISC-V processor platform. RISC-V is an open-source chip architecture, the open alternative to ARM’s proprietary designs, important because it avoids licensing dependencies on Western IP and gives Chinese manufacturers a path around US export controls on chip technology. The sector was quieter than in recent weeks.

⚡ New Energy & Materials (3 deals)

Three deals, all with undisclosed amounts. TCL’s venture arm backed an early-stage new materials company, and two strategic rounds landed in specialty chemicals and clean energy.

⚙️ Other Adv. Manufacturing (33 deals)

Thirty-three deals across optoelectronics, industrial equipment, quantum instruments, display materials, and precision manufacturing. Most were early stage with undisclosed amounts. The Hefei government continued its aggressive cluster-building, leading or co-leading rounds in advanced materials and quantum instrument companies alongside its aerospace investments.

Spotlight

DeepSeek (深度求索)

A round, ¥51B (~$7B+), valuation ~¥400B (~$55.6B)

China’s top AI lab takes its first outside money, on its own terms.

Where capital flows is where talent concentrates, where production capacity gets built, and where the next commercial technologies will come from.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

As this report went to press, China’s drug regulator accepted an IPO application from Neuracle (博睿康), the company behind the world’s first commercially approved invasive brain-computer interface. It filed for a ¥2.5 billion (~$347M) listing on Shanghai’s STAR Market, the tech-focused board that serves a similar role to Nasdaq for Chinese companies. That timing is coincidental, but the signal is not. China’s frontier medical devices are moving from lab to market to public listing faster than most investors expected.

Where the Money Went

This week’s scan captured 109 deals across all sectors, with 27 additional stragglers from last week’s gap. Origin Quantum’s ¥3 billion (~$417M) quantum computing Pre-IPO dominated the headline numbers. Strip that out and 16 deals disclosed a combined ~$443M (~¥3.2B), a solid mid-tier week. Robotics and AI continued to lead deal volume, but the week’s most interesting stories came from frontier tech and advanced manufacturing.

🧠 AI (22 deals)

AI deal flow stayed strong at 22 rounds, though this week skewed toward application-layer companies rather than foundation models. The standout was CreativeFitting (井英科技), which closed both an A and A+ round backed by Ant Group for its overseas AI short drama app, Reel.AI. HiDream.ai (智象未来) received a strategic investment from Huace Film (华策影视), one of China’s largest private TV drama producers. A cluster of early-stage deals in spatial intelligence, AI education, and virtual humans filled out the sector.

⚡ New Energy & Materials (19 deals)

Materials and new energy logged 19 deals, almost entirely early-stage. MATTERENE (烯材科技), co-founded by Nobel laureate Andre Geim, raised a Pre-A+ from Aviation Industry Investment for its graphene film production facility in Shenyang. Advanced ceramics, specialty metals, and battery materials accounted for the bulk of deals, with state-backed funds leading most rounds.

🔬 Semiconductors (18 deals)

Semiconductor deal count held steady at 18. The week’s standout was Anatrix (安纳智芯), a six-month-old Peking University spinout whose RRAM analog computing chip earned a Nature Electronics paper and a Series A led by Matrix Partners China (经纬创投). Raysees (瑞识科技), the Samsung Galaxy Ring sensor supplier, took strategic capital from GAC at a ¥3.5 billion (~$486M) valuation. Wisewave (芯潮流), which designs the high-speed data link circuits that let chips inside servers and AI clusters talk to each other at hundreds of gigabits per second, raised a Series A from Sequoia China and CITIC Securities.

🤖 Robotics (16 deals)

Robotics logged 16 deals and produced some of the week’s biggest stories. Dexmal (原力灵机) closed a B round at ¥6 billion (~$833M) valuation backed by three of China’s top large language model companies: Zhipu AI, StepFun (阶跃星辰), and SenseTime. LiberAI hit a ¥3 billion (~$417M) valuation on a Pre-A. Inspire Robotics (因时机器人) raised a C+ at ¥2.6 billion (~$361M), having shipped over 10,000 dexterous hands in 2025. Qianjue Robotics (千诀科技) raised an A round at a ¥5 billion (~$694M) valuation for its robot decision-making and planning platform.

💡 Frontier Tech (9 deals)

Frontier tech produced the week’s largest round and its strongest stories. Origin Quantum (本源量子) raised ¥3 billion (~$417M) in a Pre-IPO with China North Industries Group (中国兵器集团), a defense conglomerate, among the lead investors. A nuclear energy cluster formed: Dongsheng Fusion (东昇聚变) raised $100 million (~¥720M) to build a tokamak, a doughnut-shaped reactor that confines superheated plasma with magnetic fields to fuse hydrogen isotopes into helium, releasing energy. Its D-He3 fuel choice produces near-zero radioactive waste. Weilan Zhidian (蔚蓝支点) raised hundreds of millions of RMB for a small modular fission reactor, and straggler Dongxi Fusion (东曦聚变) raised hundreds of millions for a fusion approach that uses high-powered lasers to compress fuel pellets until they ignite. In BCI, Shenfu Jianxing (神复健行) raised ¥300 million (~$42M) at ¥1.8 billion (~$250M), the largest angel round in Chinese BCI history.

🚀 Aerospace & Defense (8 deals)

Eight aerospace deals, led by Expace (科工火箭), the commercial launch arm of state defense conglomerate CASIC, which raised ¥300 million (~$42M) in a C round. Tianmu Turbine (天目涡轮) raised a near-¥100 million (~$14M) angel for aviation engines, an unusually large angel for propulsion hardware.

⚙️ Other Adv. Manufacturing (17 deals)

Seventeen deals in optics, 3D printing, precision equipment, and factory automation. The headline was Goertek Optical (歌尔科技), which took ¥1 billion (~$139M) in strategic capital from parent Goertek and Sunny Optical at a ¥8.79 billion (~$1.22B) valuation, positioning for the AR/VR optics cycle.

Spotlight

Shenfu Jianxing (神复健行)

Angel, ¥300M+ (~$42M), ¥1.8B valuation (~$250M)

Implantable brain-spinal interfaces that help paralyzed patients walk again.

Where capital flows is where talent concentrates, where production capacity gets built, and where the next commercial technologies will come from.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

This was one of the busiest weeks of the year, with 132 deals in seven days. Two humanoid robot unicorns, a $200 million 3D AI round, and a wave of quantum deals backed by something closer to industrial policy than venture capital.

Where the Money Went

132 deals crossed the wire this week. About half published some indication of the amount raised, with 25 deals disclosing exact figures for a combined total of ~$1 billion (~¥7.5 billion). The real figure is substantially higher: most early-stage Chinese rounds never publish an amount, so treat that as a floor. The biggest individual checks went to humanoid robotics, but the broader story is breadth: every sector had at least eight active deals, and several had more than twenty.

🧠 AI (29 deals)

AI led the week by deal count, anchored by two outsized rounds. VAST (also known as Tripo AI) raised $200 million (~¥1.44B) for its 3D AI foundation model, while LightLink Tech (光联芯科) raised ¥500 million (~$69M) for optical chip-to-chip interconnect, a technology that replaces the copper wires between processors with laser light to keep up with AI compute demands. The rest of the sector split between AI agents, life science automation, and data infrastructure. Several deals went to companies building the training data that physical AI systems need: embodied intelligence is generating its own supply chain.

⚡ New Energy & Materials (17 deals)

Battery materials and energy storage continued their quiet grind. No single blockbuster, but steady capital into cathode and anode materials, lithium-ion cell makers, and advanced-materials plays. The largest disclosed amounts were modest: ¥140 million (~$19M) for a flexible photovoltaic company and ¥88.2 million (~$12M) for a lithium iron phosphate subsidiary. The sector’s capital arrives incrementally, round after round, without the headline figures that robotics and AI command.

🔬 Semiconductors (25 deals)

The second-busiest sector and the most strategically dense. A subsidiary of chip-design house Montage Technology (澜起科技) raised ¥500 million (~$69M) for switch chips that control how processors and memory share data inside an AI data center, the routing layer that determines whether thousands of chips work together efficiently or spend most of their time waiting on each other. Supercore (超摩科技) raised ¥305 million (~$42M) for processors built from smaller, stackable tiles rather than one large chip, a design that lets manufacturers match high-end performance using fabrication processes they have access to domestically. LEDA Tech (立芯软件) took ¥300 million (~$42M) for EDA tools, the software engineers use to design chips before fabrication. And at the other end of the spectrum, Sibai Chuang (偲百创) was acquired at a distressed valuation by listed RF chipmaker Wisecore for vertical integration. The stage distribution skewed early, with several angel and Pre-A rounds targeting advanced chip packaging, processors that compute directly inside memory chips, and display semiconductors.

🤖 Robotics (25 deals)

The biggest individual checks of the week. Spirit AI (千寻智能) raised ¥1.5 billion (~$208M) at a ¥18 billion (~$2.5B) valuation, its sixth round in twelve months. Astribot (星尘智能) closed a ¥1 billion (~$139M) Series B at ¥12 billion (~$1.67B). Below those flagships, capital concentrated in components and data rather than finished machines: dexterous hands, tactile sensors, force-torque sensors, tendon-drive mechanisms, and the training data that teaches robots to manipulate real objects all drew more rounds than complete humanoid systems.

💡 Frontier Tech (8 deals)

Eight deals, three of them quantum. HyQubit (华翊量子) raised its A+ from a 10-investor national syndicate for quantum computers that trap individual atoms with lasers to perform calculations. FieldQuantum (量坤科技), a five-month-old quantum-AI middleware company with no product, raised hundreds of millions at a ¥1.8 billion (~$250M) valuation. GGQuanta (国光量子) completed its third round in three months from industrial and strategic listed companies. The non-quantum deals included two brain-computer interface startups and a simulator for modeling nuclear fusion reactions.

🚀 Aerospace & Defense (10 deals)

Satellite communications, eVTOL (electric vertical-takeoff aircraft, essentially flying taxis), and space. Interstellor (穿越者) raised ¥100 million (~$14M) for crewed spacecraft that fly to the edge of space and return without entering orbit, a market aimed at space tourism and high-altitude research. SparkSpace (星火空间) took a Pre-A for liquid rockets that use electric motors to feed propellant rather than traditional turbopumps, a simpler design suited to small satellite launches. The rest was early-stage: satellite-based Earth observation, rocket propellant tanks, and UAVs. Disclosed aerospace capital was modest, about $28 million (~¥200M), but the deals are concentrated in hardware categories that take years and billions to reach scale.

⚙️ Other Adv. Manufacturing (18 deals)

The catch-all sector, and this week mostly components. Kunwei Technology (坤维科技) raised ¥100 million (~$14M) for six-axis force-torque sensors, the kind of touch-sensitive joint that lets a robot arm know exactly how hard it is pressing and adjust in real time. Servo systems, fiber-optic temperature sensors, and industrial automation filled out the list. Stage distribution was scattered: from angel rounds for polishing robots to a Series D for an optical sensing company.

Spotlight

Spirit AI (千寻智能)

A+, ¥1.5 billion (~$208M), ¥18 billion (~$2.5B) valuation

The humanoid robot company that beat global benchmarks and raised nearly ¥5 billion in three months.

It was here that CATL had built a lab to burn, freeze, overload and electrocute batteries, then document exactly how they die.

A Surge in Demand

The world adds more than a Japan’s worth of electricity demand every year. Global use is rising by about 1,100 TWh annually, up from ~700 a year over the previous decade, the fastest sustained growth in more than 10 years. The cause is the electrification of almost everything: industry, air conditioning, electric vehicles and computing.

One of the fastest-growing drivers is the AI data center.

A decade ago, a large data center drew about 50 MW. Today a single AI campus is designed for 10-20x that, and the biggest are planned for 1 GW or more, the output of a nuclear reactor, on one site. A single rack of Nvidia’s latest AI chips draws up to 140 kW, against 10-15 kW for a rack of conventional servers. A 500 MW facility running flat out uses about as much electricity in a year as 360,000 American homes, roughly the number of households in San Francisco.

OpenRouter, a marketplace that routes requests across most of the major AI models, now processes more than a quadrillion tokens a year, the units of text and data a model reads and generates, roughly 15x the volume of a year earlier. Goldman Sachs expects token consumption to rise another 24x by 2030.

The obvious counterargument is efficiency: each new generation of chips and models does more per watt. But usage is growing far faster than efficiency, so total power demand climbs rather than falls. The International Energy Agency expects data centers worldwide to roughly double their electricity use by 2030, to about 945 TWh, growing four times faster than demand from everything else.

Even so, data centers at that scale would still account for less than 3% of the world’s electricity. The total energy is not the problem. The problem is concentration: hundreds of megawatts of demand arriving at a single point on the grid, with load profiles that swing by the second, faster than any grid was designed for.

That power still has to reach the chips.

Power Struggle

Between the data center and the power it needs sit three problems, each distinct, each getting worse.

1. Power delivery is years behind demand. In the United States alone, more than 2,600 GW of generation and storage capacity sits in the interconnection queue, waiting for approval to connect to the grid. The median wait to commercial operation is about five years. Google has reported potential delays of up to 12 years. Building a data center takes 12 to 24 months. Connecting it to the grid can take three times longer. In Ireland, EirGrid restricted new data-center connections in Dublin because the transmission network could not absorb them. The queue is not just long: more than 90% of interconnection applications arrive with technical deficiencies needing multiple rounds of revision before a grid operator will even begin a study.

2. The demand itself is a new kind of problem. A conventional data center drew steady, predictable power. An AI training facility does not. Training runs ramp consumption up and down by megawatts in seconds as jobs start, checkpoint, and restart. Gas turbines, the primary source of flexible generation, take minutes to ramp. The grid was engineered for loads that change slowly and predictably. The load profile of an AI data center is unlike anything it was built to serve. It is also more expensive to run: electricity pricing penalizes peaks, and a facility whose consumption swings unpredictably pays for the spikes, not the average.

3. The cost of the mismatch does not stay inside the facility. US electricity prices rose about 13% in 2025. In Georgia, residential bills climbed roughly sixfold in two years to about $175 a month while Georgia Power proposed $15 billion in expansion driven largely by data-center demand. More than 20 data-center projects across the country have been delayed or canceled amid local opposition. In March 2026, AWS, Google, Meta, Microsoft, OpenAI, Oracle and xAI signed the White House Ratepayer Protection Pledge, committing to cover generation and grid-upgrade costs rather than pass them to households.

Batteries Lead the Charge

Batteries do not generate electricity. They store it, release it, and do both faster than any other asset on the grid. That combination solves several of the problems above at once.

1. Time-to-power. A battery system can be installed in months. Paired with on-site generation, it lets a facility begin operating while the grid connection is still years away. It also raises effective capacity beyond what the connection alone can deliver: if the grid provides 50 MW but the facility needs 200 MW at peak, the battery charges when load is light and discharges when it exceeds the connection’s limit. At the extreme, a facility goes fully off-grid with solar and batteries, bypassing the queue entirely.

2. Shock absorption. When a training run spikes or drops demand by tens of megawatts in seconds, batteries match it instantly. Turbines take minutes. The rest of the power system sees a smoother load instead of raw spikes. That smoothing saves money: batteries store cheap off-peak energy and discharge during spikes, reducing peak charges.

3. Grid services. A facility with co-located storage can provide frequency regulation and voltage support back to the grid, turning it from a burden into a resource.

4. Protecting the compute. A power cut mid-training means a lost checkpoint, potentially days of wasted work. Batteries bridge outages in milliseconds, far faster than a turbine can start, and deliver cleaner power through solid-state inverters than rotating generators produce. For racks of GPUs sensitive to voltage fluctuations, that matters.

Batteries have a hard constraint. They store hours of energy, not days. They cannot sustain a facility through a prolonged outage or replace the grid as a primary power source. Gas, grid, and eventually nuclear provide that sustained generation. But batteries are the fast-responding layer that makes the rest of the stack viable.

The Trust Problem

If batteries can do all of this, the obvious question is why the storage market is not larger. The answer is not technology, cost, or capacity.

Storage batteries and EV batteries began developing in parallel around 2009. Today the storage market is only about a fifth the size of the power-battery business. The bottleneck is proving they work. Vendors claim cycle lives and efficiencies that nobody can independently verify. Some equipment underperforms in the field. Buyers cannot tell good from bad, so they price everything as if it might be bad.

That shows up directly in what people will pay. Tesla’s Megapack sells at several times the per-Wh price of comparable Chinese storage products overseas. Tesla has five years of deployed operating data, a track record asset managers can underwrite. Chinese manufacturers, many of them technically competitive, do not. Someone has to close that trust gap.

Back to the Lab

That burned-out shipping container in Xiamen was not a failure. It was a test. The hall I walked through is one of five laboratories in what CATL and the Xiamen municipal government have jointly built as the world’s largest energy storage validation platform: the Empirical Energy Storage Technology Research Institute (实证储能科技研究院). Ten hectares, roughly RMB 3 billion, and built from the start as industry-shared infrastructure (行业共享的基础设施), open to any manufacturer willing to put its equipment through the process.

Chen Xiaobo (陈小波), the institute’s dean, describes it as a physical exam center plus hospital (体检中心加医院): install a prototype, run the full test suite, identify failures, fix them on site, iterate. Another expert called it a wind tunnel (风洞).

The five labs test a storage system the way the real world would break it:

Grid connection. A 35kV/100MVA grid simulator that tests more than 10 large containers simultaneously, simulating a 1,000-node grid topology across 15 to 60 Hz to cover domestic and international standards. A system destined for Fujian’s grid gets tested against Fujian’s actual grid behavior. The lab serves a joint State Grid (国网) / China Southern Power Grid (南网) storage innovation consortium.

High-voltage safety. Testing from 1kV to 500kV, tracing the root mechanisms of ignition and explosion under extreme voltage. The engineering goal: equipment that does not catch fire and does not explode (不起火、不爆炸).

Thermal safety and combustion. The hall from the opening scene. A 20MW calorimeter, the first of its kind, inside 100,000 cubic meters of indoor burn space. Nine large storage containers can be deflagration-tested simultaneously. This is where batteries are documented failing under thermal stress.

Environmental adaptability. Five chambers (climate, salt spray, rain, dust, environment) covering minus 50°C to 100°C, altitudes up to 7,200 meters, and full-grade dust and water protection. A container bound for the Gobi Desert or a Norwegian coast gets tested under the conditions it will actually face.

Electromagnetic compatibility. The only EMC lab in the world that can take a full 40-foot shipping container as a single unit. A 65-ton turntable, 5MW power supply, and an anechoic chamber running real high-power charge/discharge cycles. EMC testing at the scale the equipment actually ships at, not on a downsized sample.

Chen names three beneficiaries:

1. Equipment makers. Faster iteration, fewer field failures, deeper knowledge of their own products.

2. Long-term asset investors. Returns depend on uptime (带电率) and how quickly a station moves from grid connection to revenue. Validation shortens that timeline. “Real money they can actually earn” (实实在在可以赚到的钱).

3. The grid. Confidence that when a major event hits and storage needs to hold the grid up, it can.

The institute is already in talks with a European insurer about recognizing validation data. A second expert predicted a national grading body will eventually rate storage equipment on safety, reliability, and grid functionality. The chain: validated asset, rated asset, insurable asset, financeable asset class. Solar walked this path over the past decade. Storage is at the stage solar was before institutional capital flooded in.

CATL’s strategy: make the lab open, but the investment unrepeatable. The consortium model follows GB 38031, the power-battery safety standard that became a national standard through industry collaboration. Chen insists the intent is “not to block others” (不卡别人). Another expert: “it will be hard for anyone to invest in a facility this complete again.” Both are true. To reinforce the platform’s independence, CATL brought in TÜV Süd, TÜV Rheinland, CSA, and CGC (鉴衡) as co-supervisors. Storage is ~20% of CATL’s business. The lab’s value is raising the bar for the entire industry.

The Money Is Moving

Capital is already flowing. Nextpower acquired Prevalon Energy for up to $365 million in May 2026, buying into BESS and AI data-center infrastructure. Prevalon, spun out of Mitsubishi Power in 2024, has over 6 GWh deployed globally with firm contracts supporting hyperscaler data centers.

In Oregon, Aligned Data Centers and Calibrant Energy deployed a 31 MW/62 MWh battery system at a Pacific Northwest campus, the first US project where a battery was purpose-built to accelerate interconnection and bring a data center online years earlier. Operational in 2026.

LG Energy Solution signed a $1.6 billion deal with Michigan utility DTE Energy for 1.5 GW/6 GWh of battery storage across eight projects, using LFP cells manufactured in the US and Canada. LG shares surged 15% on the announcement.

In Croatia, the Pantheon AI project backed by KKR-owned Greenvolt is building a €50 billion hyperscale data-center campus with 500 MW of solar and 8 GWh of battery storage behind the meter, designed to operate fully off-grid to bypass interconnection constraints. It is the largest private US investment in Europe.

Google acquired Intersect Power for $4.75 billion, gaining 2.2 GW of operating solar and 2.4 GWh of battery storage co-located with data centers, targeting $20 billion in renewable infrastructure by the end of the decade. In Minnesota, Google partnered with Xcel Energy to deploy a 300 MW/30 GWh iron-air battery from Form Energy, the world’s largest battery by energy capacity, capable of discharging for 100 hours. Iron-air stores energy by rusting iron and releases it by reversing the reaction, a technology that directly addresses the “hours not days” constraint of lithium-ion.

Jefferies estimates that hyperscalers represent a ~20 GW BESS opportunity through 2035, with ~9 GW through 2030. BloombergNEF raised its US storage projection to 204 GW by 2035 even while cutting solar and wind forecasts.

In China the capital is flowing even faster, though across the storage ecosystem broadly rather than into named data-center deals. Chinese venture databases tracked more than 50 energy-storage-related fundraises in the first five months of 2026 alone, spanning cells, materials, systems, inverters, testing, and AI-driven power management. Sunwoda Power (欣旺达动力), one of the companies building AI-data-center-specific storage solutions, closed a RMB 1.68 billion (~$230M) C round at a RMB 26.7 billion valuation. Haier New Energy (海尔新能源) raised RMB 1 billion at a RMB 6 billion valuation. Saudi Aramco and French PE firm Eurazeo co-led a B round valuing 碧澄能源 (Bicheng Energy) at RMB 10 billion.

One startup, 京清数电 (JingQing Digital Power), a storage-inverter maker, raised three rounds in five months. 新能先锋 (New Energy Pioneer) is being funded to build battery testing services, the same layer CATL’s Xiamen lab targets. The data-center-specific market in China is forming through CATL itself: a $600 million acquisition of Zhongheng Electric for data-center power (Zhongheng’s HVDC systems already run in facilities operated by Alibaba, Tencent, ByteDance, and Baidu), a $942 million stake making it the largest shareholder of 21Vianet (世纪互联), one of China’s biggest carrier-neutral data center operators, and a 60 GWh sodium-ion order with HyperStrong (海博思创), the largest sodium deal globally. Together the Zhongheng and 21Vianet deals total roughly $1.5 billion and put CATL on both sides of the data center power equation: supply infrastructure and demand.

What This Changes

The economist George Akerlof called it a market for lemons: when buyers cannot verify quality, they price everything toward the worst case, and good products get punished. The energy storage market has exactly this problem. Akerlof’s fixes are certification, warranties, brand, and licensing. CATL’s lab is reaching for nearly all of them.

The dean called the price gap with Tesla “enormous” (巨大) and framed the lab as infrastructure for 出海 (going overseas). A credible validation record gives Chinese integrators like Sungrow, HyperStrong, and Envision bankability they currently lack. CATL’s numbers show where value is heading: ESS gross margin 26.7% against 23.8% for EV batteries, overseas revenue at 31.4%. The premium is in the validated system, not the cell.

The lab is also a competitive move, and not the only one. In EVs, CATL expanded steadily from cells into materials, components, financing, and partnerships with automakers. It did not need to control the entire industry to gain influence over it. The data center investments suggest a similar pattern: Zhongheng extends its reach into power systems, 21Vianet connects it directly to demand, and the validation lab sets the quality standard. Integrators are diversifying cell supply as the market matures. Cell leadership alone is not enough at the system layer. If validation becomes an industry norm, the early mover that built the infrastructure and co-opted the certifiers has a structural advantage, even under an open-access model. Standards may ultimately be set by neutral bodies, and the geopolitical risk on Chinese exports remains regardless of validation quality. But the lab exists, and nobody else has built one.

The burned-out shipping container is still sitting under the test structure in Xiamen, in 38-degree heat, inside a hall the size of a small aircraft hangar. It was not a failure. It was a product that went through the worst conditions anyone could engineer, and the data from its death was recorded. Before batteries become infrastructure, they have to become trusted assets. CATL is building that trust.

Where capital flows tells you where talent is concentrating, where production capacity is being built, and which technologies will reach commercial scale first.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Two moods showed up in the same week. Investors poured early money into nuclear fusion and small modular reactors, frontier energy bets priced at valuations that assume a decade of patience, while one of China’s mid-tier battery makers raised a down round at a third below its prior valuation. Long-patience bets at the frontier, a squeeze in the commodity middle.

Where the Money Went

107 deals crossed the wire this week. Of those, 31 disclosed a dollar figure, for a combined total of roughly $1.21 billion (~¥8.7 billion). Treat that as a floor, not a ceiling: most Chinese rounds, especially the early ones, never publish an amount, so the real number is well above what the disclosed deals add up to.

🧠 AI (23 deals)

The busiest sector by deal count, and the one where chips, not models, drew the money. Several rounds converged on one idea: make AI computing cheaper by routing around Nvidia rather than trying to match it head-on. Sparse-computing chipmaker Moffett AI took ¥1 billion (~$139M); its chips skip the math the network does not need, since most of the numbers flowing through a neural network are zeros that contribute nothing, so the chip does more useful work per watt. A cluster of smaller chip startups raised on the same cost-per-answer logic. Disclosed AI capital came to about $251M (~¥1.8B).

⚡ New Energy & Materials (16 deals)

The week’s largest disclosed pool, about $317M (~¥2.3B), spread across battery materials, solid-state electrolytes, and specialty materials. The standout was a markdown rather than a milestone (see Spotlight), but capital also kept flowing toward the next battery chemistry rather than today’s.

🔬 Semiconductors (11 deals)

Mostly early and mostly cheap, around $26M (~¥187M) disclosed, but strategically dense: memory-maker-backed inference chips, compute-in-memory designs (chips that compute where data is stored, avoiding the memory-to-processor shuttling that is one of the largest energy costs in AI hardware), and chip-making equipment. Listed component suppliers showed up as investors, buying a window into the startups building around them.

🤖 Robotics (20 deals)

Money concentrated in components, not finished robots. Force sensors, robot hands, the interchangeable tools a robot arm swaps at its wrist, and the data used to train machines all drew more capital than any finished humanoid. The largest disclosed robotics round, ¥1 billion (~$139M), went to a force-control arm maker rather than a humanoid brand. Disclosed robotics capital was about $235M (~¥1.7B).

💡 Frontier Tech (6 deals)

Small in count, outsized in ambition: two nuclear-fusion startups, a small modular reactor designer, a neutral-atom quantum company (one of the leading approaches to a practical quantum computer, trapping individual atoms with laser beams as the basic units of calculation), and a brain-spine implant maker. Pre-revenue, pre-prototype, and priced like proven leaders. Disclosed capital was only about $42M (~¥300M), but here the headline figures are the valuations, not the cash in.

🚀 Aerospace & Defense (7 deals)

Electric air taxis and satellite laser-communication startups led here, about $146M (~¥1.05B) disclosed. The biggest was a ¥1 billion (~$139M) round for a maker of passenger electric aircraft that take off vertically like a helicopter but run on battery motors.

⚙️ Other Adv. Manufacturing (24 deals)

The catch-all sector and the second busiest, about $196M (~¥1.4B) disclosed: industrial lasers, 3D printing, optical and inspection equipment, and consumer hardware. A ¥900 million (~$125M) raise for an industrial-laser business was the largest.

Spotlight

Sunwoda EVB (欣旺达动力)

Series C, ¥1.68 billion (~$233M), ¥25 billion (~$3.5B) pre-money valuation

The power-battery arm of a listed cell maker, raising at a steep discount.

Capital flows trace where talent is concentrating, where production capacity is being built, and which technologies will reach commercial scale first.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

The week’s largest disclosed round went to a rocket company, not an AI lab. After StepFun’s $2.5B Pre-IPO absorbed all the attention last week, capital spread wide and the most interesting deals turned up in the gaps: a Starship-architecture rocket in aerospace, a chip company building China’s answer to Nvidia’s NVLink, and a quantum computing angel round with SMIC’s foundry arm at the table.

Where the Money Went

85 deals across seven sectors. 11 disclosed exact amounts totaling $263M (~¥1.9B). Aerospace, which recorded zero deals last week, came back with the week’s biggest disclosed round at ¥500M (~$69M). The stage distribution continues the 2026 barbell: seed and angel bets at one end, a handful of larger rounds at the other, and a thin middle where Series A and B capital would normally concentrate.

🧠 AI (19 deals)

The deals cluster around infrastructure: the systems that sit between raw GPU hardware and the AI models that consume it. OriginFlow (渊澈太初) raised hundreds of millions of RMB at Pre-A for electromyography data infrastructure, capturing the electrical signals from human muscles to train robots to replicate dexterous hand movements. Approaching.AI (趋境科技) raised at a similar scale for the compute-management layer that sits between raw GPU clusters and the AI companies that rent them, scheduling which jobs run on which chips, at what priority, and at what cost. The company claims to process over a trillion tokens per day for customers including Zhipu and Kimi. DeepCybo (深度机智) raised hundreds of millions at Pre-A for PhysBrain, a system that trains robots by watching video of humans performing tasks rather than requiring expensive real-robot training data. HiDream.ai (智象未来) completed a double close, Series B and B+, reportedly with Hefei government funds backing the company across both rounds.

⚡ New Energy & Materials (10 deals)

International stories dominate. Zendure (征拓), covered in Spotlight below, raised a Series B for home energy storage systems already selling across Europe. Yanhe Solar (炎和科技) raised a Series A+ for thin, flexible perovskite solar cells, a next-generation solar technology that works in low light and can be embedded directly into consumer electronics. Yanhe Solar’s cells are already shipping to Lenovo, Signify (the company behind Philips lighting), and Dreame across more than 50 countries. Shanghai Energy Bridge (能量桥) raised at Pre-A for superconducting power distribution, a technology that transmits electricity with near-zero resistance, targeted at AI data centers where power delivery is becoming the binding constraint on how many GPUs you can run.

🔬 Semiconductors (16 deals)

The largest sector by deal count after AI. Tanwei Chiplink (探微芯联), covered in Spotlight, raised hundreds of millions at Pre-A for GPU interconnect chips. WingSemitech (隼瞻科技) raised close to ¥100M (~$14M) at angel for a chip design platform built on RISC-V, the open-source processor architecture that Chinese companies can use without licensing from any American company. Shenzhen Rayhertz Technology (镭赫技术) raised a Series A for semiconductor inspection equipment, the tools that scan chips during manufacturing to catch defects. Four angel-stage semiconductor deals reflect continued seed-level capital formation across the supply chain, from materials to packaging to sensors.

🤖 Robotics (15 deals)

Components and platforms over complete robots. AGILINK (临界点), covered in Spotlight, raised at A+ for dexterous robot hands that supply multiple humanoid manufacturers. Botshare (擎天租) raised at A+ for a platform that rents industrial and service robots by the month rather than requiring factories and warehouses to buy them outright, valued at ¥7B (~$972M), reportedly five months after founding. SEAHI Robotics (世航智能) raised at A+ for maritime robots that clean ship hulls and inspect underwater infrastructure, with the Ministry of Industry and Information Technology’s National SME Development Fund classifying the company as strategic technology. RoboParty (萝博派对), reportedly founded by a 21-year-old, raised tens of millions of dollars at angel for an open-source humanoid robot with Xiaomi backing across multiple rounds.

💡 Frontier Tech (11 deals)

Three brain-computer interface companies raised in this week’s data. See The Bigger Picture below. Juliang Guangqi (矩量光启), covered in Spotlight, raised ¥200M (~$28M) at angel for superconducting quantum computing. NeuraInsight raised a Series A from MiraclePlus (奇绩创坛), the Y Combinator-affiliated accelerator, for a structured database of neuroscience research and brain-activity data used by AI labs studying how biological intelligence works. Three synthetic biology deals covered companies engineering microbes to produce proteins, nutrients, and specialty chemicals through fermentation, an industrial process that can replace petroleum-derived ingredients in food, cosmetics, and materials with bio-manufactured alternatives.

🚀 Aerospace & Defense (7 deals)

Back from zero deals last week. Astronstone (宇石空间), covered in Spotlight, raised ¥500M (~$69M) at Series A for a reusable rocket, the week’s largest disclosed round. TransFuture Aviation (华羽先翔) raised hundreds of millions at Pre-A for an electric vertical-takeoff aircraft, with Ant Group leading what is reportedly its first investment in the eVTOL sector. Beijing Interstellar Development (星际开发) raised a Series A for a reusable orbital cargo vehicle, eight years after founding and still without a first flight.

⚙️ Other Advanced Manufacturing (7 deals)

No single thread across seven deals spanning optical eyewear, 3D printing materials, water treatment membranes, and networking equipment. Shenzhen Zhongjian Technology (众见科技) raised tens of millions at Series A for optical eyewear, backed by SEE Fund and AfterShokz (the bone-conduction headphone company).

Spotlight

Astronstone (宇石空间)

Series A, ¥500M (~$69M), ¥3B (~$417M) valuation

The engineer who helped build China’s heaviest operational rockets is now building a private Starship analog with chopstick catch.

Where capital flows tells you where talent is concentrating, where production capacity is being built, and which technologies will reach commercial scale first.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Where the Money Went

Last week’s 46 deals reflected the May Day holiday. This week brought 103 across seven sectors, confirming the Q2 2026 funding cycle is fully underway.

103 deals, 28 with disclosed amounts. Those 28 disclosed a combined $3.2B (~¥23.1B), dominated by StepFun’s ~$2.5B Pre-IPO, which alone accounts for 78%. Strip that out and the remaining 27 deals disclosed ~$706M (~¥5.1B). The true weekly total is higher. Most deals don’t publish amounts, and the disclosed figure understates actual capital deployed.

Stage distribution skews heavily early. Angel and seed rounds make up the majority across every sector, with few Series A or B companies and a handful of mega-rounds at the top. The barbell shape that has characterized China’s deep tech funding all year is intact.

🤖 Robotics (23 deals)

The week’s largest deal count, and the most fragmented. No single round dominates the way StepFun does in AI. Vbot (维他动力) raised the headline ticket at ~¥500M (~$69M) Pre-A for a consumer robot dog, but the 23 deals cover consumer companion robots, industrial embodied AI, construction robots, lawn mowers, kitchen robots, wearable exoskeletons, and component suppliers. Fourteen of the 23 were angel or seed-stage, five Pre-A or A, and four strategic or B+ transactions. One straggler: ZeroErr (零差云控, robot system core components, C+, close to ¥100M, ~$14M).

🧠 AI (18 deals, including 3 stragglers)

StepFun at ~$2.5B Pre-IPO dwarfs everything else in the sector. 奕行智能 (EVAS, RISC-V AI chips) took a strategic investment from China Mobile’s chain fund; Motion Brain (眸深智能) raised ¥300M (~$42M) Pre-A for an embodied AI brain targeting humanoid robots; ComNergy Tech (共绩科技) raised close to ¥100M (~$14M) Pre-A for idle GPU compute aggregation. Three AI stragglers were sub-¥10M angel rounds.

🔬 Semiconductors (14 deals)

SemiDrive headlines with a $100M (~¥720M) Series C. China’s most-deployed automotive SoC maker is now pivoting toward humanoid robots. 象帝先计算 raised hundreds of millions in a Series B as its near-death 2024 story converts to an IPO-prep 2026 story. RiVAI Technology (睿思芯科) closed a B+ for high-end RISC-V server processors. Fermion Technology (费勉仪器) closed a C+ for precision scientific instruments used in semiconductor and quantum research. Five of the 14 deals have disclosed amounts; government-affiliated funds led or co-led at least eight.

⚡ New Energy & Materials (16 deals)

The largest sector by deal count after robotics. Lithium Source (常州锂源) took ¥440M (~$61M) strategic investment for LFP cathode expansion. Xinta Green Energy (信塔绿能) raised ¥100M (~$14M) at angel. Multiple early-stage deals in solid-state batteries, power electronics, carbon nanomaterials, and hydrogen water tech. Greater Bay Technology (巨湾技研), the ultra-fast charging battery maker, took an undisclosed strategic round.

🚀 Aerospace & Defense (8 deals)

Zero last week, eight this week. All angel or early stage, with a combined $14M in disclosed capital. Beijing Hengxing Power (恒星力量) raised ¥100M (~$14M) at angel for space energy research; Cathay Innovation and 厚雪资本 co-led. Shenzhen Zhiyu Aerospace (执宇航天) raised tens of millions (~$7M+) at angel for small reusable launch vehicles. Shenzhen Qingwei Aviation (庆为航空) closed a Pre-A for fly-by-wire avionics and smart cockpit displays. Vision Aero (维新宇航) raised tens of millions (~$7M+) at angel for a 7-seat eVTOL targeting emergency response. Four additional deals covered satellite propulsion, aerospace electrical interconnects, and microwave remote sensing.

⚙️ Other Advanced Manufacturing (15 deals)

公大激光 / Gongda Laser headlines with a Series C, hundreds of millions RMB, for its green fiber laser technology, more on this in Spotlight. Yiktong (亦唐科技) raised hundreds of millions in a B+ for high-speed SMT pick-and-place equipment. KeenCool (云酷智能) raised close to ¥100M (~$14M) for liquid cooling equipment for AI data centers. One straggler: 时耘科技 (intelligent robots, angel).

💡 Frontier Tech (9 deals)

微元合成 / Microcyto leads with ¥1.5B (~$208M), a synbio startup that used the round to acquire a ¥900M+/year traditional factory. 雷鸟创新 / Rayneo, the global #1 AR glasses brand by unit volume, closed a C+ round of over ¥1B (~$139M) in January 2026, captured in this week’s data. Two quantum computing startups, Hangzhou Wuwen Quantum (无问清芯) and GGQuanta (国光量子), and a photonic computing chip startup, PhotonCore (光子芯力), raised angel rounds. Genlight (佳量脑科学) shows a C round at an implied ¥60B (~$8.3B) valuation and has no verifiable public presence.

Spotlight

StepFun (阶跃星辰)

Pre-IPO, ~$2.5B (~¥18B), valuation undisclosed

China’s most aggressive LLM fundraiser is heading for Hong Kong, and the companies betting on it build the phones.

The China Round is a weekly report tracking venture and strategic investment activity across China’s core technology sectors: AI, robotics, semiconductors, new energy and materials, aerospace and defense, and frontier tech.

Where capital flows tells you where talent is concentrating, where production capacity is being built, and which technologies will reach commercial scale first.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Where the Money Went

Whether you were celebrating Labor Day, Cinco de Mayo, or just enjoying a long weekend, China’s five-day May Day holiday (May 1-5) kept most dealmaking on hold.

46 deals, $2.39B (~¥17.2B) in disclosed capital across nine of them. That number needs context: Kimi’s $2B D-round accounts for 84% of the total. Strip it out and 45 deals generated $390M (~¥2.8B). AI led on deal count at twelve, with robotics close behind at ten. No aerospace deals.

🧠 AI (12 deals)

One deal dominates the entire week: Kimi’s $2B (~¥14.4B) D-round at a ~$20B (~¥144B) valuation, the largest Chinese LLM startup round of 2026. Beneath that headline, two AI infrastructure companies raised a combined ¥1B+ (~$139M+) in the same week with identical “token factory” positioning: Infinigence AI at ¥700M+ (~$97M+) and Magik Compute at hundreds of millions. Nanochap took a ¥300M (~$42M) strategic round for biomedical chips targeting visual brain-computer interfaces, a medical device company tagged as “AI” on deal trackers. The remaining deals include PixelBloom’s C-round for its AiPPT product (30M+ registered users globally), a medical LLM angel (WiseDiag, ¥65M / ~$9M), a spatial intelligence platform strategic round (XGRIDS), and four late-reported deals spanning industrial cognitive AI, AI infrastructure cloud, and AI-driven drug discovery.

🤖 Robotics (10 deals)

RoboScience pulled the largest robotics round of the week at ¥1B (~$139M) for its VLOA embodied AI platform. The remaining main-window deals are earlier-stage: Eagle Vision raised a Pre-A for bionic flapping-wing flying robots with a consumer product targeting the global hobbyist market, Westlake Robotics for civilian quadruped robots, Knownobound for industrial embodied AI targeting ship maintenance and container logistics, and underwater robotics veteran Boya Gongdao closed a D+ round. Five late-reported deals brought the sector total to ten, including a Sequoia China-backed angel in smart robots and a strategic round in core robot components backed by iFlytek Ventures and Hillhouse.

🔬 Semiconductors (8 deals)

Eight deals spanning the full chip stack, from data center networking to automotive SoCs to photonic interconnects. Yunsilicon builds what it describes as China’s first 400Gbps RDMA data center networking chip, positioning it as the domestic alternative to Nvidia’s ConnectX; ByteDance and Inspur hold strategic equity stakes. Oritek closed a C-round for automotive zone controller SoCs, with SDIC Merchants participating in every round from B1 through C and eight listed auto companies as shareholders. Siminwei drew three top-tier VCs (Oriental Fortune Capital, GGV Capital, Detong Capital) to co-lead a seed at a ¥500M (~$69M) valuation for AI inference architecture, an unusually heavy syndicate for a seed. Rhinoptix raised for TFLN photonic chips, the post-copper datacenter interconnect technology covered in the April 10 issue. Sicred continues scaling SiC power devices with 100,000+ units shipped to aerospace and defense customers.

⚙️ Other Advanced Manufacturing (7 deals)

Tachin Tech raised a Pre-A for electronic skin targeting the humanoid robot market, with core technology from Zhenan Bao’s Stanford lab. Makera closed a Series A for consumer desktop CNC machines after raising $10.2M on Kickstarter. Three smaller deals: a smart lighting company in Shenzhen (Mingyuda, ¥30M HKD / ~$3.8M), a consumer electronics angel backed by Co-Creation Ventures, and a miHoYo-backed equipment investment. Two late-reported deals added a metal 3D printing angel and a high-speed SMT equipment strategic round.

⚡ New Energy & Materials (5 deals)

BYD invested directly in battery electrolyte materials maker Huasheng Xianghe (strategic, hundreds of millions RMB), continuing its vertical integration down the EV supply chain. Hebang New Materials raised a ¥100M (~$14M) A-round for bio-based composite materials certified to EU high-speed rail standards. Three late-reported deals added carbon-based energy storage materials and emerging energy tech to the tally.

💡 Frontier Tech (4 deals)

STARTORUS closed a ¥500M (~$69M) A+ for its fusion energy reactor, crossing the $1B (~¥7.2B) valuation mark. Greencloud, a subsidiary of listed Wangsu Technology, raised for immersion liquid cooling with partnerships across Intel, Dell, and BASF. Nanoloop took a seed for sports brain-computer interface wearables at ¥10M+ (~$1.4M+). One late-reported deal: Boyin Bio raised an A-round for biomaterials from Legend Capital, CAS Advanced Industry Fund, and Cornerstone.

Other sectors

No aerospace or defense deals this week.

Spotlight

Kimi (月之暗面)

Series D, $2B (~¥14.4B), ~$20B (~¥144B)

China’s best-funded independent LLM startup hits frontier parity and raises the largest Chinese AI round of 2026.

Where capital flows tells you where talent is concentrating, where production capacity is being built, and which technologies will reach commercial scale first.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Where the Money Went

129 deals in seven days, $847M (~¥6.1B) in disclosed capital. Aerospace and defense led on dollar volume at $370M across 11 deals, the lowest deal count of any sector, driven by Volant Aerotech’s $300M Series C and Cosmoleap’s ¥500M (~$69M) Series A; no other sector crossed $200M. Robotics followed at $200M across 19 deals, concentrated in RobotEra’s single large round. The remaining five sectors generated 97 deals and under $280M combined.

🚀 Aerospace & Defense (11 deals)

Two rounds accounted for nearly all disclosed capital. Volant Aerotech closed what multiple Chinese financial outlets confirmed as the largest single round in Chinese passenger eVTOL history: over $300M, with a UAE fund (Stone) leading and Shanghai’s first city-level state capital entering. Cosmoleap closed a ¥500M (~$69M) Series A for its chopstick-catch reusable rocket (the same tower-arm booster recovery system SpaceX uses), covered by SpaceNews. The remaining nine deals are earlier stage, concentrated in urban air mobility, SAR satellite infrastructure, and UAV systems.

🤖 Robotics (19 deals)

SF Express both led RobotEra’s $200M+ strategic round and operates the company’s humanoid robots across 10+ logistics centers. The operator-as-investor structure, where the round lead is also the largest deployment partner, is defining which companies demonstrate commercial traction rather than commercial intent. LinkerBot extended its fundraising to seven rounds in 18 months after shipping 10,000+ dexterous hands. Wujie Power attracted a ¥500M (~$69M) overseas deployment contract from Envision alongside its raise, the largest overseas commercial contract signed by a Chinese embodied AI company to date. Botshare, a robot rental platform launched December 2025, completed its fourth round in 105 days.

🧠 AI (22 deals)

Creati.ai closed a $20M Series B for its Buzzy video editing product, which the company frames as “the world’s first AI Video Photoshop,” reporting $15M in ARR and 20 million+ global users. Spirit AI’s Series A+, a straggler from the April 24 batch with Alibaba as sole lead and a reported ¥5.5B (~$760M) valuation, rounds out the AI highlights. The remaining 20 AI deals are early-stage and mostly undisclosed.

🔬 Semiconductors (22 deals)

IDG Capital led a ¥500M (~$69M) Pre-Series A for Calculet at a reported ¥3B valuation, building AI processors on a chiplet architecture. With access to advanced monolithic nodes constrained by export controls, chiplet designs assembled from available process nodes are emerging as a structural workaround. The remaining 21 deals are early-stage and undisclosed.

⚡ New Energy & Materials (24 deals)

The highest deal count at 24, but only $49M disclosed. QingNa Technology raised ¥200M (~$28M) in a Series A for sodium-ion batteries, with one million large cylindrical cells shipped to European customers in January 2026 and five million contracted for the year. The remaining 23 deals are early-stage and mostly undisclosed.

⚙️ Other Advanced Manufacturing (22 deals)

22 deals, almost entirely undisclosed. Cangzhou Four STARS Glass, a 33-year-old pharmaceutical glass maker, closed the only disclosed round at ¥300M (~$42M) Pre-IPO. The remaining deals are concentrated in industrial automation, precision testing, and manufacturing equipment suppliers, the enabling layer beneath the robotics and semiconductor sectors above it.

💡 Frontier Tech (8 deals)

TuringQ completed a Series B+ for photonic quantum computing, reaching an estimated ¥7B (~$970M) valuation on the strength of ¥100M+ (~$14M) in signed orders in H1 2025 and approaching ¥1B (~$138M) raised in 2026 alone. BCDTEK closed a Series A for silicon-based OLED microdisplays (the display technology inside the Apple Vision Pro) while building China’s first 12-inch silicon OLED fab.

Spotlight

Volant Aerotech (沃兰特航空)

Series C, over $300M (~¥2.16B)

The largest single round in Chinese passenger eVTOL history: UAE capital leads, Shanghai’s first city-level state investor enters, and the order book stands at over 1,900 aircraft.

Where capital flows tells you where talent is concentrating, where production capacity is being built, and which technologies will reach commercial scale first.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Where the Money Went

111 deals in seven days, $1,020M (~¥7.3B) in disclosed capital, and 95 of those 111 deals didn’t disclose. All the visible money concentrates in a handful of large rounds: robotics ($419M) and AI ($504M) collected 90% of the total while generating fewer than 40% of the deals. Semiconductors ran the highest deal count of any sector at 23, but almost none disclosed amounts, operating early-stage and quiet.

🤖 Robotics (18 deals)

Sudu Technology came in at a reported $2B+ valuation at 11 months old and demo stage; X Square Robot collected all four of China’s internet giants on a single cap table at ¥2B (~$278M) Series B. The bottom of the distribution is a long tail of ~$690K seed rounds for pre-product startups building everything from dexterous hands to explosion-proof industrial quadrupeds. The component layer sits between them: Motorevo shipped 100,000+ joint modules in 2025 and is still valued at ¥1.6B (~$222M). The stage distribution skews to the extremes, with large late-stage rounds and a long tail of sub-¥10M seeds, but few companies in between.

🧠 AI (24 deals)

EVAS closed the week’s largest AI round at ¥1.5B (~$208M) with four Beijing municipal funds co-leading simultaneously, one day after Beijing formally established the ¥20B (~$2.8B) four-fund structure that backed the round. Sunrise AI (曦望) extended its run to seven financing rounds in ~16 months, crossing ¥10B (~$1.4B) valuation as China’s first inference-GPU unicorn. Loopit’s $50M (~¥360M) round (Garena lead) follows the app reaching #1 on the global Google Play Entertainment chart.

🔬 Semiconductors (23 deals)

The highest deal count of any sector, but almost none disclosed. The sector’s early-stage density is running well ahead of its public capital story. Two companies warrant attention regardless: NanoLN (晶正电子) is raising Pre-IPO financing as the holder of approximately 78% of global lithium niobate thin-film wafer supply, a material foundational to 5G filters and photonic chips. Wendun Juxin (稳顿聚芯) shipped China’s first domestic high-precision compound-semiconductor stepper in September 2025 and is already profitable. Neither has significant English-language coverage.

⚡ New Energy & Materials (13 deals)

Zero disclosed capital across 13 deals. Sodium battery, flow battery, and advanced materials companies raising without announcing terms. Luquos Energy (易池新能, CUHK spinout) is the exception, a Hong Kong-registered flow battery company with international backing (Towngas + Gobi Partners) that chose to disclose.

🚀 Aerospace & Defense (10 deals)

The National Strategic Emerging Industry Investment Fund (国调基金) made a strategic investment in Chang Guang Satellite that accounts for most of the sector’s visible capital, a state-capital substitute for the financial and foreign investors who exited after Chang Guang was placed on the US Treasury’s SDN (Specially Designated Nationals) sanctions list. FAW Group’s eVTOL spinout Qiyi Technology (旗翼科技) added the week’s largest angel-stage aerospace deal at ¥400M (~$55M).

⚙️ Other Advanced Manufacturing (20 deals) · 💡 Frontier Tech (3 deals)

Audfly (清听声学) stands out in Other Adv. Manufacturing with a Series B+ at ¥2B (~$278M), a directional audio company backed by Lenovo Ventures. Frontier Tech had just three deals: a synthetic biology Series A from PAML Biotechnologies (柏垠生物, Hillhouse-adjacent capital) and a fusion-wire JV from Juneng Superconducting (聚能超导).

Spotlight

EVAS (奕行智能)

Series B, ¥1.5B (~$208M)

China’s first reportedly mass-produced RISC-V AI chip, now backed by Beijing’s four-fund industrial apparatus.

Inclusion AI built a model for the agent economy, where thousands of tasks run in loops, every output token costs money, and the model that wastes the least wins. Very few labs optimize for intelligence per output token, despite it being one of the most important metrics in agentic AI. We ran tests against two comparable open-source models. Ling was the only one to complete all of them.

The Token Explosion

OpenRouter processed 20.6 trillion tokens just last week.

That’s roughly 2.4 million complete works of Shakespeare.

Per day.

The driver isn’t chatbots. It’s agents. Anthropic’s own data: agents use roughly 4x more tokens than chat interactions. Multi-agent systems use 15x. Platforms like OpenClaw are running tasks around the clock. As Anand Iyer of Canonical VC put it: “The demand for AI inference right now is coming from agentic platforms, especially OpenClaw.”

At this volume, every wasted token is real money. Claude Sonnet 4.6 alone processed 1.38 trillion tokens last week on OpenRouter. The OpenRouter State of AI report puts average prompt tokens at 6,000 per request versus 400 for completions, a 15:1 input-to-output ratio. Applied to Sonnet’s traffic, that works out to roughly $5.2M at list price ($3/M input, $15/M output) across one platform in seven days.

The Overthinking Problem

The industry’s answer to “make it better” has been “make it bigger.” The result: top models now use tens of millions to hundreds of millions of output tokens to complete the same evaluation on the Artificial Analysis Intelligence Index. The arms race has been chasing intelligence scores while ignoring what it costs to get them.

Users have noticed. “Caveman prompting” strips grammar from inputs to force shorter outputs. The instruction prompt: “Speak primitive. Use nouns and verbs. No grammar filler. Save tokens.” A formalized Claude Code skill built around the technique has 14,000 GitHub stars. Its README written in the style it teaches: “Brain still big. Cost go down forever. One rock. That it.” Across real dev tasks, it cuts output tokens by 65%. It works for coding. It breaks on anything that requires sustained reasoning.

At the corporate level, the opposite problem: tokenmaxxing. Companies began tracking employee token consumption as a productivity metric. Workers compete on internal leaderboards ranked by tokens burned, with the highest individual user averaging 281 billion tokens. Volume confused for value.

The instinct isn’t limited to prompt engineering. Marc Andreessen recently called a YouTuber with “a hundred videos on retardmaxxing” his “new life coach.” The philosophy: go to work, do a good job, come home. Don’t overthink it. Chamath Palihapitiya said the same on All-In: “Enjoy your life, work hard, and don’t overthink it.”

Caveman prompting is the demand-side version of this: users forcing models to stop overproducing. But the hack reduces cost without reducing waste. A model that produces fewer tokens because it reasons more efficiently is a different proposition from one that’s been told to shut up. What if a model just didn’t overproduce by design?

The Intelligence Yield Thesis

“Bigger is better” has peaked. The new competition is fewer active parameters, faster inference, lower cost per completed task.

Mixture-of-Experts architectures route each token to a small subset of the total parameters. What matters is how many fire per token, not how many exist. Linear attention scales computation linearly instead of quadratically, an advantage that compounds as outputs get longer.

The focus should be on outcome per token.

Ant Group and Ling-2.6-flash

Ant Group’s dedicated AGI lab was launched in February 2025, inspired by DeepSeek’s research model. Their stated vision: “AGI as humanity’s shared milestone, not a privileged asset.”

Ant Group’s DNA is financial inclusion: 140 million healthcare users on AQ, 60% from cities where specialist care barely exists; 1.69 million farmers with satellite-assessed, collateral-free loans processed in minutes. Chairman Eric Jing calls it “inclusive AI.”

Ling-2.6-flash is in our opinion one of the models on the Pareto frontier of the Intelligence Yield Thesis. (We’re also big fans of Minimax M2.7, which leads in a different quadrant).

The architecture: 104 billion total parameters, 7.4 billion active per token. MoE with 256 expert modules. Hybrid Linear Attention + Multi-head Latent Attention with linear time complexity, where the advantage grows at longer outputs. Multi-Token Prediction for parallel inference.

The efficiency: 15 million output tokens to complete the full Artificial Analysis eval. The comparison models used 5-7x more.

Before anyone knew who made it, Ling launched on OpenRouter as “Elephant Alpha.” Topped the trending charts. Hit 100 billion daily token calls. Top 8 by total calls on the platform. Without brand or marketing, the model proved itself.

First, some context on benchmark results before we dive into the tests (images from artificialanalysis.ai).

The Benchmarks

Token use

Nemotron used 110 million output tokens to complete the standardized AA Intelligence Index. GPT-OSS used 78 million. Ling used 15 million. That’s 86% fewer tokens than Nemotron and 81% fewer than GPT-OSS.

Cost

Multiply by price per token. Ling: $23. GPT-OSS: $67. Nemotron: $145.

Model Pricing

Cheap per-token pricing doesn’t guarantee cheaper outcomes. GPT-OSS charges 2x more per output token than Ling ($0.60 vs $0.30) and uses 5x more output tokens. Factor in input costs and the total comes to $67 vs $23 for the same evaluation.

Intelligence

This is the chart where Ling looks weakest. Intelligence score: 26, against GPT-OSS’s 33 and Nemotron’s 36.

The benchmark results call to mind a quote by someone who knew a thing or two about intelligence.

The AA Intelligence Index measures general reasoning, knowledge, and math. It does not measure sustained execution in loops, tool use across hundreds of steps, or the ability to finish what it starts. In testing, Ling was the only model that did.

Let the Tokens Do the Talking

Three tests, run through Claude Code: qualitative analysis, bug fixing, and visual code generation. Ling against two open-source models in the same weight class: Nemotron-3-Super-120B (12B active), Inclusion AI’s own published benchmark rival, and GPT-OSS-120B, OpenAI’s open-source entry. Same prompts, same tools, same environment. Every token tracked.

Qualitative Analysis

For this test we wanted to check qualitative verbal reasoning in addition to simple tool calling. Each model was given a one-paragraph brief and asked to grab the latest news and produce a vibe check on today’s tech: sources, an overall vibe read, companies vibing and not vibing, and a one-paragraph synthesis. Take a position, back it with reasoning, and convey it in an output file, blind-scored by Gemini 3.1 Pro on voice, judgment, and second-order thinking.

• Ling 2.6 Flash: 18/50: Finished in 2,579 tokens, 50.7 seconds. Hedged every observation, described the surface without reading beneath it.

• GPT-OSS-120B: 21/50: Similar tone. Generic vibe call, headline-obvious picks. Gemini flagged both for consultant-speak. Better discipline score kept it three points ahead.

• Nemotron 3 Super: Did Not Finish (DNF): Never started. Couldn’t parse the setup step and emitted garbled Python-serialized output instead of clean bash. Repeated the same broken command 11 times, mid-loop it ran echo and pwd successfully, proving basic bash execution was fine, then immediately returned to the broken pattern. Same serialization bug that surfaced in all three tests. 4,145 tokens spent, nothing produced.

Bug Fixing

Ten programs from QuixBugs: classic algorithm implementations, each with exactly one introduced bug. The task: find the bug, fix it, pass the tests.

• Ling 2.6 Flash: 10/10: Fixed all ten. On knapsack, a large input triggered a test harness timeout. Ling identified the performance constraint and refactored iterative DP to recursive with @lru_cache, going beyond the one-line fix to make the algorithm pass within the test harness timeout.

• Nemotron 3 Super: 5/10, DNF: A serialization bug appeared across all three tests: instead of clean code output, the model produced Python-serialized data structures. It worked around this for the first five programs. On Levenshtein distance, the bug triggered an infinite loop it never escaped.

• GPT-OSS-120B: 5/10, DNF: Fixed every program it attempted (gcd, flatten, mergesort, quicksort, find_in_sorted), all correct on first try. Then stopped. After program five, it output a summary of remaining tasks and quit. We relaunched it to confirm: same result. No error, loop, or technical failure, it simply didn’t sustain the task.

Visual Code Generation

Breakout game, single-file HTML. One prompt, no follow-ups.

• Ling 2.6 Flash: Functional: 503 lines. Glow effects, particle physics, working game mechanics. No debugging, no reconstruction, no workarounds. Played immediately.

• GPT-OSS-120B: Broken on delivery: 294 lines. The game logic was there (paddle, ball, bricks, collision, particles) but it didn’t work out of the box: the start screen overlay blocked click events from reaching the canvas, so the game couldn’t actually be started without a code fix. Simpler than Ling’s output: flat-colored bricks, minimal effects, smaller canvas. Same mid-task stall as the other two tests: froze mid-generation, required prompting to continue.

• Nemotron 3 Super: Broken: Same serialization bug as in the bug-fixing test. Produced Python-serialized data instead of HTML. The game logic was there but was buried inside a model-level format failure that affected all three tests. We reconstructed it from the raw output; the logic held up pretty well once extracted. Though there were layout bugs.

The Results

Across all three tests, Ling was the only model to complete every task without intervention. The competition failed in different ways: Nemotron’s serialization bug blocked it in every test. OSS was competent when working (every bug fix correct) but stalled mid-run across all three tests, each time requiring a prompt to continue, and its visual output didn’t work without a code fix. Completion and token efficiency moved together.

A model that uses fewer tokens per step can sustain more steps before losing coherence. The same design discipline that cuts token waste also cuts task abandonment. The tradeoff showed in qualitative analysis, where Ling scored lowest: a model trained to minimize output tokens will hedge rather than elaborate, summarize rather than argue. The same discipline that makes it fast at execution makes it flat on opinion.

The AA Intelligence Index doesn’t test what agents actually do. The benchmarks that do tell a different story. BFCL-V4 measures function calling accuracy: Ling 67.04, GPT-OSS 43.3, Nemotron 35.12. TAU2-Telecom measures multi-step task completion: Ling 93.86, Nemotron 62.94, GPT-OSS 41.45. SWE-bench Verified: Ling 62.00, Nemotron 61.00, GPT-OSS 43.80. MRCR long-context: Ling 54.01, Nemotron 39.04. Ling leads on agentic benchmarks across the board. It trails Nemotron on hard math (AIME 73.80 vs 88.59).

Different tool for a different job.

Why This Is Important

Andrej Karpathy’s autoresearch makes this concrete. A coding agent autonomously improves a training script in a loop: read, hypothesize, edit, run, evaluate, repeat. Unattended. Karpathy ran it for two days: 700 experiments, 20 discovered optimizations, 11% training speedup. Shopify CEO Tobi Lütke tried it overnight: 37 experiments, +19%.

Each cycle: roughly 18,000 tokens at about $0.10. At 700 cycles, the gap between an efficient model and a verbose one is the gap between a $70 run and a $700 run.

The same pattern applies everywhere agents run in loops: CI pipelines, code review, data monitoring, agent swarms. The emerging architectures don’t use one model for everything. Frontier models like Kimi K2.6 and Claude Sonnet are strong at complex reasoning and high-stakes decisions. But running them on every sub-task in a multi-agent pipeline is expensive by design. Kimi K2.6 at $0.75/$3.50 per million tokens, Claude Sonnet at $3/$15. Efficient models handle execution-layer throughput at a fraction of the cost.

A swarm running hundreds of sub-tasks needs each sub-agent to be reliable, cheap, and disciplined, not the smartest model available. At $0.10/$0.30 versus $3/$15, that choice determines whether a pipeline is economically viable at scale.

The cost floor dropping changes what’s possible. Always-on agents that monitor, iterate, and improve without human intervention. A researcher annotating genomic data in a continuous loop. A solo developer running hundreds of test variations overnight. A clinic in a mid-tier city running diagnostic pipelines on a budget that would not have supported it a year ago. The compute and models exist. The constraint has been a reliable model with good cost per token at volume.

Ling at $0.10/$0.30, open-source, designed to minimize waste. That’s the financial inclusion bet applied to intelligence itself.

20.6 trillion tokens last week. The agent economy is here. Efficiency is the core driver. Inclusion AI is building for it.

Where capital flows tells you where talent is concentrating, where production capacity is being built, and which technologies will reach commercial scale first.

The China Round is free, published every Friday, and written for investors, operators, and founders tracking where China’s tech capital is moving and why it matters.

About the author: Dermot McGrath is Irish, based in Shanghai, a decade in China’s tech and investment ecosystem, fluent Mandarin. Co-founded a VC fund scaled to nine-figure AUM. Now running ZenGen Labs, a cross-border strategy studio covering AI, robotics, and deep tech.

Where the Money Went

102 deals from April 10 to 17. $1.63 billion (~¥11.7B) in disclosed capital across 27 of them — the other 75 went undisclosed. Robotics commanded $937 million (~¥6.75B) of that, across 23 deals. This week, though, the more interesting pattern runs underneath the headline numbers: listed companies and OEM customers are entering venture rounds not as passive financial investors but as strategic acquirers, buying equity positions in their key suppliers before commercial volumes arrive.

🤖 Robotics (23 deals)

它石智航 (TARS Robotics) closed a $455 million (~¥32.8亿) Pre-A, reportedly the largest private embodied AI raise in Chinese history, with Hillhouse, HongShan, and Meituan co-leading 14 months after founding. The stage distribution across the batch forms a barbell: eight angel and Pre-A rounds ran alongside five B+ or strategic rounds, with almost nothing in between.

🧠 AI (17 deals)

The bulk of the disclosed capital — ¥5亿+ (~$70M+) — went into one company: 智象未来 (HiDream.ai), which released an MIT-licensed open-source image model before closing this round. The broader batch skews early, with Anhui, Hefei, and Beijing municipal capital prominent as co-investors.

🔬 Semiconductors (23 deals)

The sector’s headline event was not a venture round. 盛合晶微 (SJ Semiconductor, 688820.SH) listed on the STAR Market 2,700 times oversubscribed, reaching a ¥360亿 (~$5B) market cap at issue, with ¥47.79亿 (~$664M) in net proceeds. As the #1 domestic 12-inch chip bumping provider and holder of 85% share in mainland 2.5D advanced packaging, it controls a chokepoint that every Chinese AI chip designer needs to reach production. Among the private rounds, 芯擎科技 closed a B+ at approximately $100 million (~¥720M) for its automotive cockpit chip platform, pulling in Yutong Bus (600066.SH) as a strategic co-investor, extending the company’s addressable market beyond passenger EVs.

⚡ New Energy & Materials (14 deals)

A quieter week for the sector. 疆海科技 (Zendure), which sells energy storage hardware across 63 countries and counts Europe and North America as its primary markets, raised a round led by domestic strategic investors. 顺铉新材, a specialty polyimide film producer with export relationships into South Korea, Japan, the US, and Russia, closed a materials round. Neither disclosed amounts.

🚀 Aerospace & Defense (9 deals)

边界智控 (Boundary.AI) closed a B-round for its eVTOL flight control systems — the only Chinese company to have cleared CAAC’s SOI#1 airworthiness review for eVTOL-specific FCS. The rest of the batch was light: several pre-A rounds for drone platforms and satellite sensor startups, mostly undisclosed.

⚙️ Other Advanced Manufacturing (12 deals)

Mixed batch with no standout cluster. 锐能科技 raised a B-round with 菱电电控 (688667.SH) acquiring 30% as a strategic lead. Several other industrial automation plays closed early-stage rounds with regional government funds, consistent with the ongoing manufacturing digitization push in non-coastal provinces.

💡 Frontier Tech (4 deals)

量旋科技 (SpinQ) — announced April 3, flagged in this week’s straggler batch — sells superconducting quantum computers commercially into 200+ institutions across 40+ countries and raised ¥6亿 (~$83M) in a C+, several months after closing its C-round, bringing the combined C-series total to approximately ¥10亿 (~$139M). The company is profitable and building out a pre-IPO syndicate with Guotai Junan Innovation and Chengdu state capital as new investors. NovaFusionX (诺瓦聚变) appears in this week’s data with its ¥7亿 (~$97M) 天使+ round but was covered in last week’s issue; refer to that report for the full analysis.

Spotlight

TARS Robotics (它石智航)

Pre-A, $455M (~¥32.8亿), valuation ¥120.58亿 (~$1.67B)

Humanoid robotics, 14 months old, betting against the VLA consensus.