Connexion
Executive Summary:
Chinese firms are languishing under a compute crunch due to U.S. export controls restricting access to high-end GPUs. Domestic manufacturers like Huawei, Cambricon, Biren Technologies, and others have yet to fill the gap. Yet, the People’s Republic of China (PRC) has not waited for these constraints to disappear before pushing its domestic computing ecosystem overseas. More broadly, Chinese academics, policy elites, and industry figures have begun calling for domestic “compute going global” (算力出海), even though advanced computing power remains limited at home (PKU Institute of Urban Governance, April 30). Shenzhen’s artificial intelligence (AI) action plan, released in early September, similarly calls for domestic foundational hardware to expand abroad as part of an integrated Chinese AI ecosystem (Shenzhen Municipal Bureau of Industry and Information Technology, September 4).
Beijing appears to be laying the groundwork to export computing power before technological and supply constraints are resolved. Chinese-language sources suggest that this contradiction stems from a simplistic conception of the PRC’s “compute crunch.” Instead of waiting for domestic supply constraints to erode, Chinese firms and policy elites appear increasingly willing to internationalize the PRC’s computing ecosystem even while those constraints remain (China Brief, June 11). Overseas deployment can open new markets, bolster demand for Chinese technology, and establish Chinese hardware, software, and technical standards internationally. While exporting compute may entail a short-term opportunity cost at home, Chinese actors appear increasingly willing to bear that cost in pursuit of long-term technological and commercial gains.
Deploying Compute Abroad
Physical deployment is only one form of Chinese compute going global. Chinese analysts distinguish it from the more mature model of “services crossing the border” (服务出境), in which computing hardware remains in the PRC while domestic data centers process AI workloads for foreign customers and export the resulting tokens and services (Zhong Lun, July 10). Even when hardware remains physically in the PRC, compute exported-as-a-service still represents a decision to devote computational resources to foreign rather than domestic demand. Computing capacity is inherently rivalrous: capacity devoted to processing foreign workloads cannot simultaneously be used for domestic workloads.
The model of cross-border compute exports has already developed into a wider industry push. At the 2026 World Artificial Intelligence Conference (WAIC), one exhibitor established a dedicated English-language “Token going global” (Token出海) section that demonstrated Chinese computing power packaged into standardized tokens services and exported overseas, attracting considerable attention from foreign attendees, particularly from the Middle East (Jiemian News, July 19; China Brief, July 22). In 2025, the China Academy of Information and Communications Technology (CAICT), the think-tank under the PRC’s Ministry of Industry and Information Technology (MIIT), collaborated with industry partners to launch a dedicated “Computing-Power Token Going Global Ecosystem Initiative” (算力词元 (Token) 出海生态计划). Its aim is to move the sector beyond experimental projects towards “standardized, efficient, and sustainable” (规范、高效、可持续) overseas expansion (CWW, July 1). Its organizers argued that doing so could help hedge against external risks and expand services trading (Open Data Center Committee, July 1).
Importantly, Chinese firms are actively laying the groundwork for the physical deployment of advanced domestic AI hardware abroad. Huawei has drawn up plans to export Ascend-series chips, including the Ascend 950DT and 950PR AI accelerator, to South Korea and has signed distributor agreements with local partners like Hansol PNS and SK Shieldus (Sina Finance, July 7). The company has also unveiled the Atlas 960E SuperPoD as part of its effort to address large-scale AI infrastructure demand overseas, while other Chinese companies have announced plans to deploy a “domestic computing power cluster” (出海国产算力集群) in Saudi Arabia (SenseTime, July 20). Similar intent is emerging vis-à-vis Southeast Asia, with reports that Malaysia is considering adopting Huawei’s 910C Ascend in its sovereign AI ambitions (Sina Technology, September 8).
Chinese elites have endorsed a wider version of this push. Wang Zhongyuan (王中原) of Fudan University has argued that the PRC should assist countries in the Global South by constructing local computing infrastructure, jointly building data centers, and exporting “computing services” (算力服务) (CASS, July 16). Song Guoyou (宋国友), deputy director of Fudan University’s Center for American Studies, is even more explicit, calling for Chinese firms to deploy “computing clusters” (算力集群) across different regions of the Global South (National Office for Philosophy and Social Sciences, July 16).
Building Overseas Markets for Chinese Compute
A growing number of Chinese industry and policy elites have explicitly described internationalization as the next stage for the domestic compute industry. Li Wei (栗蔚), deputy director of CAICT’s Cloud Computing and Digitalization Research Institute, has called for accelerating the overseas expansion of the domestic computing-power industry and integrating it into the “global computing-power industrial system” (全球算力产业体系) (People’s Tribune, July 20). Wang Chao (王超), executive director of CAS Star, the deep-tech venture capital firm founded by researchers from the Chinese Academy of Sciences, has similarly argued that domestic compute will not only serve domestic demand but also for overseas expansion (Beijing Daily, September 23).
Chinese companies have described similar ambitions. Huawei has actively touted Ascend and its Kunpeng computing platform as having created “a new choice for the world” (为世界构建了新的选择) (Huawei Tech, February 2024). iFlytek, meanwhile, has partnered with Huawei Ascend to “cooperate deeply on overseas large-model deployments” (在海外主权大模型上深度合作) and “plant flags and seize positions around the world” (在全球插红旗、抢阵地) (iFlytek, April 29). Other firms describe computing power going global as the “industry’s second growth curve” (Runze Intelligence, August 28) and argue that overseas expansion “is no longer optional, but imperative” (Sina Finance, July 29).
Southeast Asia has become a particularly important potential market. One CAICT report constructed a market-entry evaluation framework for overseas expansion and identified opportunities for Chinese computing-power providers in emerging markets, especially in Southeast Asia, where they note surging demand (CWW, May 13). One Chinese AI infrastructure company similarly concludes that compute in Southeast Asia will exceed 3GW in 2026 and 6GW in 2028, asserting that Chinese firms should leverage their accumulated technological capabilities to “rapidly enter overseas computing-power center markets” (快速切入海外算力中心市场) and “capitalize on the supply gap” (把握 … 供给缺口) in Southeast Asia’s high-end IDC market (Runze Intelligence, August 28). Meanwhile, Sugon, another major Chinese computing-infrastructure provider, has established an ASEAN business headquarters in Nanning, Guangxi. By providing a Chinese tech stack comprising Sugon’s servers and its high-end Hygon DCU compute, PRC firms can provide a “complete solution” for Southeast Asian countries (QQ News, September 21).
Chinese hardware providers often achieve pricing advantage by undercutting foreign competitors. One Chinese estimate concludes that for equivalent computing services yielding similar inference performance, Chinese compute providers can charge just one-fifth to one-seventh as much as comparable overseas services. The price advantage is derived partly from lower electricity costs in the PRC and vertical integration of large Chinese telecommunications operators, most of which own both computing and network infrastructure (Southern Daily, June 5).
Compute Crunch Unevenly Distributed
The PRC’s overseas push is happening despite domestic compute constraints. Chinese sources depict a landscape in which shortages are concentrated in select types of high-performance hardware, while the country’s aggregate computing infrastructure expands rapidly.
Yang Siwei (杨思维) and Liu Rui (刘睿) of CAICT have written that the PRC’s domestic computing buildout has “laid a solid foundation for the computing-power industry to ‘go global’” (为算力产业“出海”奠定坚实基础) (Information and Communications Technology Policy, March 2025). By the end of 2023, the PRC already possessed more than 230 exaFLOPS of computing capacity, accounting for over 25 percent of the global total. Meanwhile, intelligent-computing capacity grew 70 percent, accounting for 30 percent of the PRC’s overall computational scale. By June 2024, more than 250 intelligent-computing centers were operating or under construction nationwide (Information and Communications Technology Policy, March 2025). Li Wei points to further growth since, claiming that the PRC has developed sufficient computing capacity to support 70 percent of domestic parallel-training demand for trillion-parameter models (People’s Tribune, July 20). Consequently, Yang and Liu call for Chinese firms to start building “comprehensive computing-power service ecosystems” (全面算力服务生态) in emerging country markets (Information and Communications Technology Policy, March 2025).
Importantly, Chinese firms do not need to physically ship domestic AI chips abroad to internationalize domestic computing power. Developers overseas can, for example, access Ascend computing power from the PRC through PyTorch, a software framework for developing and running AI models that reduces friction when accessing hardware (Beijing Daily, September 23).
The PRC has already experimented with this model at scale. In April 2026, the Shantou Overseas Chinese Pilot Zone in Guangdong completed the PRC’s first end-to-end commercial model for “Token going global,” which included consolidating the first phase of an international Token factory with 2,000 petaFLOPS of computing capacity (TYM, September 3). This represented a deliberate decision by Chinese authorities to add compute capacity with the express intent of serving the overseas market.
Overseas users have since accessed token services produced in Shantou, which Chinese reporting describes as the first time Chinese computing resources were exported in the form of “high value-added digital services” (高附加值的数字服务) (CWW, April 23). Zhu Jun (朱军), director of the Basic Theory Research Center at Tsinghua’s Institute for AI, described the “international Token-factory model” (工厂的建设模式) as a practical path for Chinese produced computing power and large models to expand into overseas markets (TYM, September 3). The economics of the model are increasingly plausible as the hardware itself remains in the PRC. In Shantou, network latency to Singapore reportedly fell to just 32.7 milliseconds, allowing overseas users to submit requests to models running on Chinese infrastructure and receive outputs with low network delays (Southern Daily, June 5).
Chinese researchers have also explored architectures that reduce dependence on the most high-performance accelerators. Zheng Weimin (郑纬民), a professor at Tsinghua University and former president of the China Computer Federation, has described an inference architecture in which a 10,000-accelerator cluster might employ 9,000 domestically produced accelerators for prefill and 1,000 higher performance accelerators for generation, raising the domestic share to 90 percent. [1] Zheng remarked that the resulting high-quality tokens could serve both domestic industries and go global, adding that the PRC had “sufficient computing capacity” (算力充足) to achieve this in addition to a clear cost advantage (Ningbo Computer Federation, June 10).
Hardware Internationalization Uplifts Entire Industry
Chinese inference services explain one part of the story, yet their viability makes the planned export of advanced Chinese accelerators even more puzzling. If Chinese companies can serve overseas customers while leaving their hardware within the PRC, there is less reason for them to physically export valuable hardware to foreign markets.
One answer is that overseas demand can feed back into the development of the PRC’s domestic technology ecosystem. Guo Liang (郭亮), Chief Engineer at CAICT’s Cloud Computing and Big Data Research Institute, has observed that emerging markets in Southeast Asia, the Middle East, Africa, and Latin America offer market conditions that have created ample room for the PRC’s computing services to expand overseas. More importantly, he argues that transitioning from building infrastructure toward exporting capabilities and services can promote the “iterative upgrading” (迭代升级) of the PRC’s “computing-power industrial chain” (算力产业链) and drive the coordinated, concurrent uplifting of domestic AI computing clusters, large models, and AI chips (Xinhua, July 24).
Liu Xiaoge (刘小鸽), a deputy director of research at the Development Research Center of the State Council, has similarly argued that Token exports can create a powerful “demand-pull effect” (需求牵引效应) that helps mitigate technological chokepoints affecting the PRC’s domestic AI hardware stack. Supplying domestically produced chips for large-scale application scenarios, he argues, will create opportunities for frequent iteration that can narrow gaps with the international frontier “in both manufacturing processes and ecosystems” (制程与生态) (State Council, May 8).
Conclusion
The overseas ambitions of Chinese firms do not demonstrate that the PRC has overcome its computing constraints, nor does it mean that Chinese companies can challenge Nvidia globally at a competitive scale. Chinese legal analysts have pointed out that Chinese firms targeting overseas markets should prioritize cross-border service exports from infrastructure located in the PRC before deploying physical hardware abroad (Zhong Lun, July 10). Huawei’s own leadership has been forthcoming about these constraints. Rotating chairman Eric Xu recently acknowledged that domestic shortages prevent a “fully-fledged” rollout of Huawei Ascend abroad (Reuters, September 17).
This qualification matters. Huawei is constrained from international expansion on a “fully-fledged” scale, but this does not mean that internationalization has stopped altogether. Chinese companies and policy elites do not appear to view compute scarcity as a reason to postpone international expansion before compute parity is achieved. As time progresses, and as the PRC consolidates increasingly novel algorithmic efficiencies, its ability and willingness to export compute abroad will only grow.
Notes
[1] Prefill processes the input prompt while generation produces output tokens, with the two stages having different compute requirements. This allows them to run on different types of accelerators.
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Executive Summary:
Policymakers in the People’s Republic of China (PRC) want to improve “data supply” (数据供给) to “provide sufficient ‘fuel’ for the development and application of artificial intelligence” (为人工智能发展和应用提供充足“燃料”). This is according to a new plan from the National Data Administration (NDA, 国家数据局) titled “Implementation Plan for Promoting the Construction of High-Quality Industry Datasets” (关于推进行业高质量数据集建设行动的实施方案). Published on June 8, the plan aims to create a “data flywheel” to accelerate the construction of a “symbiotic ecosystem in which data factors and artificial intelligence evolve synergistically” (建数据要素与人工智能协同演进的共生生态) (NDA, June 8).
One speculative part of the plan calls for “exploring a value system based on tokens” (探索以词元 (Token) 为基础的价值体系). This is part of a commercial push to make data-related products economically viable, which policymakers believe will dramatically improve the development of the AI sector in the People’s Republic of China (PRC). The plan therefore directs industry to “explore new trading models such as token trading, and build a data value system based on tokens that is quantifiable and priceable” (探索词元交易等新型交易模式，构建以词元为基础，可量化、可定价的数据价值体系) (NDA, June 8).
The wording around tokens (词元) in the plan is tentative but significant. This is because it is the first time that the digital token has been given an official, standardized Chinese name and definition. It was only in March that NDA director Liu Liehong (刘烈宏) announced that the Mandarin word ciyuan (词元) would be used officially to denote digital tokens. In an address delivered at the China Development Forum, Liu described tokens as “settlement units” (结算单位) connecting technological supply with commercial demand that are “measurable, priceable, and tradable” (可计量、可定价、可交易) (People’s Daily, March 25). The importance of tokens—the basic unit through which large language models (LLMs) process information—to artificial intelligence (AI) applications has prompted Beijing to define, standardize, and regulate them before any real market emerges.
Token Centrality Leads Beijing to Take the Initiative
Token consumption has become a key indicator of demand for AI infrastructure in the PRC. The rise of agentic software that carries out multi-step tasks by planning, calling tools (drawing on external programs such as web search, code, or databases), and checking and revising its own output, has pushed token consumption far above that of a simple chatbot exchange (Anthropic, November 26, 2025, March 24). China CITIC Bank (CITIC; 中信银行) estimates that a single task for an AI agent consumes 10–100 times the number of tokens of a standard chatbot session (WeChat/@CITIC Securities, April 15). The PRC’s recent nationwide “lobster farming” (养虾) craze, in which users deploy and continuously run the open-source agent OpenClaw, was a catalyst for growing demand for inference compute and cloud services. [1] The ensuing surge in token usage has led to a “compute shortage” (算力荒), rising cloud prices, and demand for domestic inference chips, according to CITIC (WeChat/@Huatai Securities, March 13; WeChat/@CITIC Securities, April 15).
Beijing has moved quickly to define the regulatory environment around the token economy after its rapid emergence. After Liu defined tokens and the token economy in March, the NDA has moved to produce an implementation plan for the sector in roughly two months—including a month-long public comment period, during which state media raised public awareness about the “ciyuan economy” (WeChat/@China Economic Times, April 17, April 21, April 27, April 28). This official coverage makes clear that Beijing views tokens as more than an accounting unit within the LLM technology stack. Tokens are an instrument that can link datasets, model services, and compute resources across an entire emerging sector.
Setting Standards and Picking Winners
Without waiting for dedicated legislation, Beijing is applying existing tools to govern the token economy. On the positive side, the state backs compliant intermediaries as the legitimate operators of token services. For example, the NDA has spotlighted Guizhou Data Bao (贵州数据宝), a former enterprise compute provider that has pivoted to selling token services from Gui’an’s (贵安新区) state-backed data center cluster, where its daily token calls roughly quadrupled in three months (NDA, April 10). On the negative side, it constrains higher-risk intermediaries through existing rules on AI services, data exports, anti-money laundering, and foreign exchange. For instance, in June 2026 the Ministry of State Security (MSS) publicly warned that unregulated “AI relay stations” (AI中转站), single-interface resellers of access to various domestic and foreign models, pose data security- and national security-related risks (Wechat/@MSS, June 8). Legal commentators had already flagged one such platform, B.AI, which was launched by controversial crypto entrepreneur Justin Sun (孙宇晨), as potentially violating the Interim Measures for the Management of Generative AI Services (生成式人工智能服务管理暂行办法) and the PRC’s cross-border data-export rules (Cyberspace Administration of China, July 10, 2023; National Business Daily, May 12). [2]
Price oversight may be the next front, though it remains at the proposal stage. After Alibaba Cloud, Tencent Cloud, and Baidu AI Cloud all raised prices for compute within a ten-day window, researchers at the National Development and Reform Commission’s Institute of Market and Price Studies argued for a monthly token price index and a billing disclosure regime (WeChat/@China Economic Times, May 18). The government is yet to formally propose such a mechanism, however, and state media still describe the token economy’s pricing and regulatory framework as under construction (Xinhua, June 2).
Beijing’s moves so far have been about who may operate in the token economy. Whether the token can also be traded and priced is a separate question. The NDA implementation plan’s call to “explore ciyuan trading” is an early move toward it, expanding the current data trading regulatory regime to tokens and building on the 2022 “Twenty Articles on Data” (数据二十条), released jointly by the Party Central Committee and the State Council, which allowed for data trading even when ownership is unclear (MOFCOM, December 2, 2022).
One of the main problems for developing a token trading system is figuring out how to price tokens (WeChat/@Journal of Modern Commercial Banking, March 26). An intuitive approach would be to set prices based on token volume. Some services, such as OpenRouter, trade freely using per-token pricing for AI usage. This approach is unlikely to lead to a large, liquid market, however, as token value is shaped by an array of additional factors beyond volume, meaning that services that consume more tokens are not necessarily worth more (WeChat/@China Economic Times, April 21; CSDN, April 27). The NDA’s framing of “ciyuan trading” which anchors the value and exchange of data on the token, is therefore unlikely to become a liquid market soon.
The NDA’s approach is more likely driven by a desire for control. By making the token a common valuation tool, it places datasets, model services, and compute within a single comparable system. A state-led system for measuring and evaluating AI services based on the token is already being built. The China Academy of Information and Communications Technology (CAICT), a research institute under the Ministry of Industry and Information Technology (MIIT) that serves as the sector’s main standards body, recently upgraded its evaluation system for model-as-a-service (MaaS) platforms into a dedicated “Token Service Evaluation System” (Token服务评估体系). This broadens assessment from a platform’s model capabilities to the quality, performance, reliability, and metering (tracking how many tokens are used) of its token services (WeChat/@CAICT, April 14). In defining what counts as a competent token service, CAICT is setting the standards for the ciyuan economy. These standards in future could become de facto benchmarks for government procurement, state-owned enterprise (SOE) cloud adoption, and industry certification. Setting those standards before any market exists defines the requirements that every token-service operator will eventually have to meet.
State Guidance for Token Services
Chinese policymakers consistently emphasize the need to create use cases and applications for emerging technologies. The same goes for the ciyuan economy. As an article in the Party journal Study Times recently put it, AI competition is evolving from a race over model parameters to an engineering contest over “who can put models to use” (谁能把模型用好) (Study Times, May 13). State-owned China Telecom has moved fastest to occupy the model application layer, in early May launching Xingchen (星辰) TokenHub, a one-stop platform for aggregating models, routing requests, and metering and operating token services. This hub is tied to its Xirang (息壤) compute scheduling system and provides everything from raw compute to token delivery (WeChat/@State-Owned Assets Report, May 8). The company’s chairman, Ke Ruiwen (柯瑞文), has cast this as a “strategic choice” (战略选择) to move from “selling traffic” (卖流量) to “selling tokens” (卖token) (WeChat/@LinkitmeCloud, April 30). [3] In mid-May, all three state telecom operators launched retail token plans, with China Telecom’s starting at renminbi (RMB) 9.9 ($1.45) per month for 10 million tokens (National Business Daily, May 17).
China Telecom has convened an industry body, the Token Ecosystem Alliance (Token生态联盟), to pull more than 20 compute, model, security, and application partners onto its own platform and, in its words, “expand the token ecosystem” (做大词元生态) beyond its in-house services (NetEase, April 30). Company executives describe the alliance as a way to anchor that ecosystem around itself (C114, April 29). This illustrates a degree of coordinated competition under state direction. [4] The alliance gathers central SOEs, cloud platforms, model vendors, and chipmakers whose interests are far from aligned under the banner of “national cloud, national chips, national models” (国云、国芯、国模). [5] China Telecom wants to be the hub; Huawei wants to expand its Ascend chip ecosystem; Alibaba Cloud already runs its own stack; model vendors such as Zhipu AI (智谱) and iFlytek (讯飞) want distribution; and domestic chipmakers want access to the mainstream service layer (WeChat/@CITIC Securities, April 15; WeChat/@FaxAI, May 12). In practice, the alliance pools partners’ models, compute, and applications onto China Telecom’s platform. For a model vendor or chipmaker, joining the alliance is the way to secure both customers and a foothold in the emerging stack before its standards, routing rules, and entry points are settled. For China Telecom, which can now control access to the enterprise and government orders for which those vendors compete, the alliance cements the centrality of a powerful SOE (C114, April 29). The token-service layer, in other words, is where measurement standards, platform power, and industrial alliances converge, and where SOEs, by convening and coordinating, can influence the platforms that reshape the industry.
Numerous PRC firms are seeking to carve out space in the AI sector’s platform layer. The nascent state of this layer, with standards and entry points yet to be defined, means that its key players are yet to establish themselves. Infinigence AI (无问芯穹) is a good example of an emerging platform firm. It is a service provider, offering compute for AI inference that uses both Western and Chinese hardware, and currently hosts more than 160 models (WeChat/@ChinaVenture, May 6). Unlike Western chips such as those designed by Nvidia and AMD, many domestic chips do not come with mature software ecosystems, creating the space for intermediaries like Infinigence to translate the fragmented field of PRC chips into usable inference services (Rand, June 26, 2025). Infinigence has backing from numerous leading investors in the PRC technology space and recently raised more than $100 million in a round led by local state capital and industrial investors. The company has rebranded itself from a “compute operator” (算力运营商) to “China’s token economy hub” (中国 Token 经济枢纽), signaling its ambitions (WeChat/@ChinaVenture, May 6). This is an early signal that token infrastructure is becoming a distinct asset class that local state capital is moving to own—another channel through which the state shapes the emerging ciyuan economy.
Conclusion
A new economic sector, the ciyuan economy, is emerging rapidly in the PRC. Shaped by NDA policy and CAICT’s evaluation criteria, platform companies are moving into the space, often with the backing of significant investments. A mature ciyuan economy is a long way off, however, as important questions remain on how tokens will be priced, and what compliance framework will be constructed.
The state’s swift mobilization to regulate this new sector—before a market has had time to fully develop—is the inverse of the process in the United States. There, the token economy has run ahead of the state and regulation has stayed deliberately light. Each approach has its strengths and weaknesses. In light of these differences, the ultimate effects of the PRC’s concerted efforts to shape the country’s AI inference activity toward its preferred goals will be an important story in U.S.–PRC AI competition in the years ahead.
Notes
[1] “Lobster farming” is a Chinese internet meme referring to the deployment and use of the open-source AI agent OpenClaw. OpenClaw became known as “little lobster” (小龙虾) because its icon resembles a red lobster; “Lobster farming” refers to users configuring, fine-tuning, and continuously running the agent on a personal computer or cloud server so that it can perform workflows through messaging apps or other interfaces. After OpenClaw became a viral phenomenon in the PRC, local governments and tech companies quickly moved to support the trend. Shenzhen’s Longgang District (深圳龙岗区) issued the “Ten Lobster Measures” (龙虾十条), while Wuxi High-Tech Zone (无锡高新区) introduced twelve measures to support OpenClaw and related open-source community projects. These policies included computing-power subsidies, deployment services, application vouchers, and providing several million RMB in funding for so-called “one-person companies” (OPC; 一人公司) (CCTV, March 9). Major PRC tech firms, including Tencent, Alibaba, Baidu, ByteDance, Huawei, and Xiaomi, also lowered the barrier to “lobster farming” through cloud deployment, one-click installation of OpenClaw-like products, and domestic software and hardware adaptation (36Kr, March 11; Alibaba Cloud; Baidu Qianfan Cloud; Tencent Cloud; Volcengine; accessed May 14).
[2] Private AI API relay platforms like B.AI operate in a legal gray area. They forward domestic users’ prompts and business data to overseas models while operating outside the PRC’s formal compliance channels. Beyond the generative AI measures noted in the text, this can also trigger cross-border data obligations under the Measures for Security Assessment of Data Exports (数据出境安全评估办法) and the Measures on Standard Contracts for the Export of Personal Information (个人信息出境标准合同办法) (Cyberspace Administration of China, July 7, 2022; Office of Central Cyberspace Affairs Commission, February 24, 2023).On social media, the owner of a private API relay platform claimed that he had been detained by Shanghai police for 37 days for operating a gray-market relay service and is now out on bail pending trial while facing criminal charges. The authenticity of this claim, however, has not been independently verified (X/@YesterdayBigcat, May 13).
[3] China Telecom has not fully monopolized this layer of the token economy. Around the same time as it released its Xingcheng TokenHub, NetEase Youdao (网易有道) released a platform called ThinkFlow and China Mobile released its own platform, MOMA. Both platforms are neutral aggregation and routing platforms rather than LLMs, which distinguishes them from similar offerings such as Alibaba Cloud’s Bailian (阿里云百炼) and Tencent Cloud’s Token Plan, which are tied to those firms’ own model and cloud ecosystems (WeChat/@FaxAI, May 12).
[4] This pattern has appeared repeatedly in the PRC’s strategic industries, including electric vehicles, photovoltaics, and 5G telecommunications. Beijing sets the direction and builds a common framework, multiple firms compete within that framework, and the state retains coordinating authority over standards, certification, and market access. See Naughton, Barry, The Rise of China’s Industrial Policy 1978 to 2020, Universidad Nacional Autónoma de México, 2021.
[5] Participating companies included China Electronics Corporation (中国电子), China Mobile, CRRC (中车集团), Huawei, ZTE, Alibaba Cloud, Zhipu AI, iFLYTEK, Hygon Information (海光信息), Moore Threads, and MetaX (WeChat/@Cailian AI Daily, April 30).
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