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华尔街日报Codex · 实盘可交易 · 做多市场:A股▲ 赚 +0.64% · 已结算 · 2 腿均把握 5/10
北京时间·🕒 发布 09:00:00时区推断·⟳ 抓取 09:05:46·⚡ 决策 07-24 09:09:14 +3m28s·95.3 天前

WSJ称中国正以国家背书推动AI用户转向国产AI芯片,华为昇腾供给仍是瓶颈

WSJ新增披露副总理层面对大型AI用户施压使用国产芯片,边际上强化国产算力从主题到真实采购迁移的预期。

📄 原文华尔街日报↗ 原文
Inside China’s All-Out Push to Catch Up With American AI Chips
China is executing a state-backed campaign to develop domestic AI chips to rival leading U.S. chips. Chinese Vice Premi…
ENTER▲ 做多航天电器002025.SZ🇨🇳小仓
▲ 赚 +2.47%入场 07-24 当日开盘 @64.05 → 离场 07-27 开盘 @65.90
60.0080.0064.05做多 07-24离场 07-2707-0209-04
日 K 取自复盘打分切片 · 蓝点/蓝虚线 = 纸面入场价 · 灰虚线 = 纸面离场 · 持有期红底 = 赚(价格在入场线上方)、绿底 = 亏
💡 交易逻辑政策施压国产芯片,做多昇腾连接器弹性腿
怎么买 限价买入 不高于昨收 +3%、2 个交易日内有效
怎么卖 止盈 +5%(半仓)/+10%(清仓) · 止损 -5% · 时间止损 3日
ENTER▲ 做多中航光电002179.SZ🇨🇳试探仓
▼ 亏 -1.18%入场 07-24 当日开盘 @33.78 → 离场 07-27 开盘 @33.52
35.0040.0045.0033.78做多 07-24离场 07-2707-0209-04
日 K 取自复盘打分切片 · 蓝点/蓝虚线 = 纸面入场价 · 灰虚线 = 纸面离场 · 持有期红底 = 赚(价格在入场线上方)、绿底 = 亏
💡 交易逻辑昇腾950放量强化,连接器液冷核心供应商受益
怎么买 限价买入 不高于昨收 +3%、2 个交易日内有效
怎么卖 止盈 +4%(半仓)/+8%(清仓) · 止损 -4% · 时间止损 3日
不做 寒武纪(688256.SH)
虽是国产AI芯片主标的,但市值约7847亿元且7月20日至21日主线已反复交易,本次WSJ报道缺少公司级订单增量,追主标的edge不足。
不做 海光信息(688041.SH)
国产替代方向同向,但市值约7252亿元且近期波动拥挤,本次报道不能量化到海光订单或收入增量,不做。
不做 中芯国际(688981.SH)
制造环节受益链条成立但市值超1.2万亿元,WSJ报道未给中芯订单或产能增量,短线弹性不足。
不做 北方华创(002371.SZ)
设备端逻辑偏长期,且7月21日已涨停、7月22日继续上涨,本次报道不是设备订单催化,避免追拥挤主线。

另有 3 腿,见展开详情。

展开详情(成交明细 / 研究档案 / 原文全文 / 决策记录链)

其余 3 腿

不做 高新发展(000628.SZ)
华鲲振宇标签相关但未查到本次昇腾950订单级证据,13周趋势持续下行且20日跌27.56%,不做。
不做 拓维信息(002261.SZ)
华为生态相关但未查到本次昇腾950直接订单证据,估值高且走势偏弱,不如做更明确的连接器弹性腿。
不做 神州数码(000034.SZ)
系统集成联动不如连接器/液冷直接,且7月22日至23日已上涨,本次新增edge有限。

分时走势

做多 002025.SZ 航天电器

建仓日早于近 30 天,只有日线图

做多 002179.SZ 中航光电

建仓日早于近 30 天,只有日线图

成交明细 · 纸面

做多 002025.SZ 航天电器

收益状态+2.47% 已平仓
进场成交2026-07-24 · 当日开盘 · @64.05
离场成交2026-07-27 · 开盘 · @65.9
毛收益+2.89%
成本+0.42%
净收益+2.47%
计入收益+2.47%
建仓日2026-07-24 · 进场不早于新闻时刻 + 2 分钟

做多 002179.SZ 中航光电

收益状态-1.18% 已平仓
进场成交2026-07-24 · 当日开盘 · @33.78
离场成交2026-07-27 · 开盘 · @33.52
毛收益-0.77%
成本+0.41%
净收益-1.18%
计入收益-1.18%
建仓日2026-07-24 · 进场不早于新闻时刻 + 2 分钟

收益口径 event_time_plus_2min_10min_walk_open_topup_to_next_open_exchange_calendar_fill_model_local_notional_v9 · method_id m8db1cbc8f2d · 截至 2026-10-27 15:33

研究档案

🔎 新鲜度:最早出现 2026-07-23 · 扩散 medium · price-in 风险 medium ↗ ↗ ↗

消息传播链

  1. 2026-07-20行业媒体转载阿尔法派/内部KB非一手原文 ↗
    WAIC后市场已开始讨论昇腾950超节点亮相和国产算力链,说明底层主线并非完全新鲜。
  2. 2026-07-21行业媒体转载长江军工/内部KB非一手原文 ↗
    纪要点名昇腾950牵引国产算力建设,并提到中航光电、航天电器在高性能模组、铜连接及液冷的布局。
  3. 2026-07-23 21:00 ET首发Wall Street Journal非一手原文 ↗
    WSJ披露中国高层推动大型AI用户采用国产芯片,并给出华为AI芯片出货、国产替代目标等新增叙事。
    市场反应:A股当时盘前未开,核心国产算力股7月23日普遍下跌,未见本报道已交易。

关键理由

  • WSJ新增披露副总理层面对大型AI用户施压使用国产芯片,边际上强化国产算力从主题到真实采购迁移的预期。
  • 内部KB显示昇腾950 2026年出货预期70万至100万片,航天电器和中航光电被长江军工列为国产算力24G高性能模组、铜连接及液冷前瞻布局标的。
  • 量级上,昇腾950若按70万至100万片放量,将把国产超节点连接器/液冷从小批验证推向批量供货;航天电器市值约300亿元、中航光电约716亿元,二阶弹性优于寒武纪/海光/中芯等超大市值主线票。

主要风险

  • 这不是官方新规而是WSJ深度报道,且WAIC昇腾950与国产算力链已在7月20日至21日被机构反复讨论,存在高开兑现风险。
  • 国产AI芯片仍有性能差距和产能瓶颈,WSJ也称英伟达顶级芯片算力约为华为最好产品4倍,若资金只交易一日情绪容易回落。

反向证据

  • 做多前查反向 · 来源 kb_search · 日期 2026-07-23 · 影响 weakens
    KB与WSJ均提示国产AI芯片仍存在性能差距和产能瓶颈,属于削弱追高和重仓的反证。
    检索:国产AI芯片 近期 利空 产能不足 性能差距 华为昇腾 反向证据 原文 ↗
  • 做多前查反向 · 来源 kb_search · 日期 2026-07-24 · 影响 weakens
    未命中高新发展与本次昇腾950放量的订单级证据,且报价显示20日跌幅较大,故不作为主腿。
    检索:高新发展 华鲲振宇 昇腾950 Atlas 950 订单 市占 字节跳动 原文 ↗
  • 做多前查反向 · 来源 kb_search · 日期 2026-07-24 · 影响 weakens
    未命中拓维信息本次昇腾950订单级新证据,更多是华为生态主题联动,降低优先级。
    检索:拓维信息 昇腾950 兆瀚 华为 昇腾 AI一体机 订单 原文 ↗

历史先例(按相似度)

  • 相似度 8/10 688256 2026-07-08 Reuters称DeepSeek开发自研AI推理芯片,国产算力自主可控主题被交易。 原文 ↗
    事件后 +1日 +8.6% · +2日 -1.0% · +3日 -1.7% · +4日 -0.2% · +5日 -4.7%
    相似度依据:同为A股国产AI芯片自主可控催化,标的是直接芯片龙头但当前拟交易的是二阶连接器。
  • 相似度 8/10 688041 2026-07-08 Reuters称DeepSeek自研芯片后,国产AI芯片龙头被同步交易。 原文 ↗
    事件后 +1日 +6.0% · +2日 +2.9% · +3日 +0.6% · +4日 -0.6% · +5日 -5.5%
    相似度依据:同市场同机制,海光信息代表国产AI芯片龙头反应,但市值与二阶弹性不同。
  • 相似度 7/10 688981 2026-07-08 DeepSeek自研芯片催化下,国产半导体制造链同步交易。 原文 ↗
    事件后 +1日 +13.7% · +2日 +7.2% · +3日 +7.5% · +4日 +5.8% · +5日 +1.0%
    相似度依据:同为国产半导体链,但中芯国际是制造环节且市值更大。
  • 相似度 7/10 002371 2026-07-08 DeepSeek自研芯片催化下,国产半导体设备龙头同步交易。 原文 ↗
    事件后 +1日 +9.5% · +2日 -0.2% · +3日 -4.7% · +4日 -3.5% · +5日 -7.4%
    相似度依据:同为国产半导体链二阶,但北方华创更多是设备端,当前更偏昇腾系统连接器。
  • 相似度 7/10 688256 2026-04-30 DeepSeekV4后市场交易国产模型原生适配华为昇腾、寒武纪、海光闭环。 原文 ↗
    事件后 +1日 +7.4% · +2日 +9.9% · +3日 +3.7% · +4日 +5.3% · +5日 +12.1%
    相似度依据:同为国产模型与芯片生态闭环重估,但当时更偏模型适配而非政策压力。
  • 相似度 7/10 688041 2026-04-30 DeepSeekV4后国产AI芯片生态闭环被资金交易。 原文 ↗
    事件后 +1日 +16.3% · +2日 +15.3% · +3日 +9.1% · +4日 +17.9% · +5日 +17.9%
    相似度依据:同市场同主线,但交易对象为芯片主标的而非二阶供应商。
工具调用 · 历史记录,结果未知(6 种)
  • search_processed_events · 结果未知
  • query_modeling_kb · 结果未知
  • kb_search · 结果未知
  • stock_quote · 结果未知
  • price_snapshot · 结果未知
  • event_study · 结果未知

原文全文

展开原文 · 15,370 字
China is executing a state-backed campaign to develop domestic AI chips to rival leading U.S. chips.

Chinese Vice Premier Ding Xuexiang warned the country’s largest AI users that anyone who resisted employing domestic chips was a traitor.

Huawei is leading the domestic push, but Nvidia’s top AI chip still boasts four times the computing power of Huawei’s best offering.

This summary was generated with AI and reviewed by an editor. Read more about how we use artificial intelligence in our journalism.

China is executing a state-backed campaign to develop domestic AI chips to rival leading U.S. chips.View more

Last summer, top Chinese chip developer Huawei Technologies held a closed-door briefing for the country’s technology czar to introduce its latest artificial-intelligence chips. The company laid out a plan for rivaling American behemoth Nvidia and said China could become self-sufficient in some critical areas of AI within three years.

It was just what Ding Xuexiang, a confidant of Chinese leader Xi Jinping, wanted to hear. Three years earlier, Washington had squeezed China’s access to cutting-edge AI chips and the tools required to manufacture them—a potentially crippling blow to the country’s ambitions as a tech power. With Xi’s blessing, Vice Premier Ding started a fevered effort to forge domestic alternatives.

Ding dusted off the same all-out approach China had used to produce its first atomic bombs, hydrogen bombs and satellites in the 1960s during a rift with the Soviet Union. He set up a committee that drew from the country’s best companies and labs to form specialized teams and directed them to master the different elements of the chip supply chain.

Huawei’s report on its progress gave Ding leeway to be more aggressive. He delivered a blunt warning to China’s largest AI users, according to people familiar with the message: Anyone who resisted employing domestic chips was a traitor.

In May, Huawei went public with more details of its plans. The company already led the way in reducing China’s dependence on foreign AI chips from 90% in 2021 to less than 60% by 2025, and the newer designs could help lower that number to 25% over the next half-decade, according to data from Morgan Stanley. What’s more, Huawei said it had figured out workarounds for making near state-of-the-art silicon without leading-edge machinery.

“If the U.S. hadn’t forced our country, our company and our industry into a corner, we would never have done something like this,” said Huawei deputy chairman Eric Xu.

In AI software, China is giving the U.S. an unexpected run for its money. Last week, Beijing-based startup Moonshot AI unveiled a new model, Kimi K3, that closely trails the performance of top models from American AI giants OpenAI and Anthropic. Xi delivered a speech positioning China as the global champion of open, accessible AI. Shares in U.S. chip makers fell.

In hardware, however, China still lags far behind the U.S. even with Huawei’s recent progress, and chip-production capacity problems are preventing Chinese companies from deploying AI as quickly as they would like. Moonshot had to pause sign-ups for premium services just two days after launching K3 because it didn’t have enough computing capacity.

The outcome of China’s effort to catch up has ramifications for the global economy. If the U.S. controls the top technology, the rest of the world will depend on Washington’s favor to make progress in fields such as medicine, robotics and autonomous driving—not to mention weaponry and military strategy. AI advances depend on hardware, in particular the chips that train AI models and help them tackle everyday tasks.

A record of overtaking the West in electric vehicles and batteries gives many in China confidence the country can eventually break the U.S. stranglehold on chip technology. But chips are different from other hardware. The technology is extraordinarily complex, and it is moving at a lightning pace.

“It’s trying to catch up with a bullet train,” said Kyle Chan, a fellow at the Brookings Institution. Even at “full China speed,” he said, it’s a daunting challenge.

Ding’s committee bets that by hitching China’s engineering prowess to the engine of state capitalism, it may eventually get there. The push has made progress that few thought possible back in 2022, when Huawei was starved of U.S. technology and Chinese AI companies depended almost entirely on Nvidia.

China’s State Council Information Office didn’t respond to requests for comment.

Executives at Chinese tech companies described a change in mindset over the past year. They had previously dismissed local chips as impossibly far behind. Now they think they can do business with Huawei and other local chip makers. Tech company Meituan recently released an AI model that it said was comparable to Google’s flagship model and was trained solely with Chinese chips.

In memory chips, another key AI need, Chinese companies that barely had sales a few years ago can now catch a glimpse of the American and South Korean companies at the front of the pack.

Chinese chip makers aim to boost the production of advanced wafers used to make chips to more than 500,000 a month by 2030, up from roughly 30,000 last year, according to people familiar with the target. Huawei expects to ship around 1.5 million AI chips this year, roughly doubling its 2025 volume, some of them said.

Still, the technology gap remains considerable. Nvidia’s top AI chip boasts around four times the computing power of Huawei’s best offering. China’s AI computing power stood at around 14% of the U.S. in 2025, research house Bernstein estimated. Despite China’s aggressive build-out, Bernstein expected China would remain significantly behind the U.S. through 2030.

Under Ding’s watchful eye, Chinese companies are using hundreds of thousands of Nvidia chips to stay within striking distance of their American rivals for now.

All out or die

In 2022, the Biden administration instituted export curbs that aimed to slow China’s progress in AI for military uses. They blocked China from purchasing advanced AI chips and tightened access to the top-end, ultraviolet lithography machines and other tools needed to produce them.

Communist Party leaders saw the controls as a threat to its capacity to boost economic growth and compete globally with the U.S. They didn’t yet grasp the promise of large language models like ChatGPT, which OpenAI had just released, but they saw dominance of AI in its many forms as critical to China’s security and the party’s legitimacy.

The chip committee headed by Ding, a 63-year-old who trained as a metalworking engineer, kicked off in early 2023. It identified critical fields—such as advanced manufacturing and packaging, high-bandwidth memory and chip-design software—and recruited top teams in each. They also started deciding which companies would get access to the nation’s limited supplies of chips.

China’s earlier efforts to build a self-reliant domestic chip industry had been marred by corruption and hobbled by bureaucratic mandates. Officials were determined to correct those mistakes. The government encouraged chip-related companies to pursue stock-market listings so they could raise more capital and be subjected to market discipline. Even Huawei would face competition from cloud-computing companies developing their own AI chips.

The government scrapped state salary caps for state-owned equipment maker Naura Technology, allowing the company to lure top talent from foreign rivals.

The Ding plan had a rough first year. Dozens of homegrown AI chips were available on the market, but a government-backed research lab told Premier Li Qiang that they were “very unstable,” according to state media. None were good enough to train large-scale models.

Beijing worried about the reliance of the country’s AI developers on Nvidia. Chinese engineers were locked into Nvidia’s software tools, which could barely be used with domestic chips. The American chip giant had tailored products for China that sat right at the performance limit set by U.S. export controls. Chinese firms also bought banned Nvidia chips from middlemen who routed shipments through other countries.

China’s central economic planning agency brought in several academics and chip experts to help run the project, an unusual move for top government bodies which usually keep decision-making in-house. In 2024, China raised about $48 billion in a state fund to invest in its semiconductor industry.

Turning point

The turning point came last year. Huawei readied a new chip, the Ascend 950, that surprised early testers with its performance. Others, including cloud-computing and AI giant Alibaba, also reported promising progress with their own chips.

Around that time, Nvidia Chief Executive Jensen Huang flew to Beijing with approval from President Trump to sell a downgraded chip designed for China called the H20. In Washington, Commerce Secretary Howard Lutnick said on television that letting China buy Nvidia’s “fourth-best product” would keep the country hooked on American technology.

Ding and other senior officials felt insulted, people familiar with the matter said. Authorities privately told companies to halt their Nvidia purchases, while officials publicly raised cybersecurity concerns about the U.S. company’s products.

Nvidia wanted to win back Beijing. In December, Trump said he told Xi he would allow sales of the company’s more powerful H200 chip. But in Beijing, the calculation had shifted. Chinese officials called in tech companies—sometimes weekly—to evaluate how vital the H200 truly was. In January, Beijing told some companies they could buy the H200s only when necessary, while demanding a commitment to use more domestic chips.

The squeezing of Nvidia boosted demand for domestic chips, creating a supply crunch as Chinese chip makers struggled to ramp up production. It also led to a new boom in the gray market.

Over the past six months, prices for smuggled Nvidia chips have more than doubled, according to Chinese distributors, due to tightened U.S. enforcement and shipping delays in the Middle East. Some Chinese companies have managed to amass clusters of Nvidia’s cutting-edge Blackwell chips. Others are leasing computing power from foreign data centers.

Tech workarounds

Huawei’s efforts to work around such technology restrictions date to 2019. The company had designed an Ascend AI chip that, on paper, matched Nvidia’s top chip at the time, but it never got to produce the chip en masse. Weeks later, the first Trump administration blacklisted Huawei’s chip unit, cutting off its access to U.S. chip technology.

That meant the Chinese company could no longer work with Taiwan Semiconductor Manufacturing, the only chip maker capable of mass-producing the Ascend. He Tingbo, chief of Huawei’s chip division, called it her unit’s “darkest hour.”

Since then, Huawei has increasingly turned to alternative designs, advanced packaging and networking technology to squeeze computing power from older machinery—a practice industry insiders dub “diaohua,” or fine-carving.

Leading-edge chips are made using extreme-ultraviolet, or EUV, lithography systems. The machines use focused beams of ultraviolet light to etch on wafers of silicon billions of transistors roughly the width of a strand of DNA. Tinier processes allow for smaller transistors, meaning more circuitry can be squeezed onto a single sliver of chip to boost computing power. The cutting-edge 3-nanometer process can fit 250 million to 300 million transistors in one square millimeter of silicon.

Because of U.S. export curbs, China has access only to previous-generation deep-ultraviolet, or DUV, machines, which can’t etch with as much precision. Huawei has developed a multistep method for producing 7-nanometer chips using DUV, but it complicates circuit layouts, introduces more opportunities for error and slows output.

The Wall Street Journal reviewed some 200 patents published over the past two years by Huawei and its partners. Those patents illustrate their efforts to reduce errors and boost yield from older machinery through production workarounds and software, sometimes using AI.

One patent describes a wafer-holding plate that can detect and adjust surface temperatures to correct flaws caused by old machinery. It isn’t clear how many of those patented processes are in use on the factory floor.

Huawei revamped the design for its latest Ascend 950 chip, making it more cost-effective. Chinese AI companies including DeepSeek helped Huawei make the chip easier to use. They said it has improved significantly over previous generations and can now effectively substitute for Nvidia chips on certain tasks—particularly inference, where trained models respond to user queries. That is persuading more Chinese companies to use it for AI applications such as the AI assistants.

Huawei also seeks to parlay decades of networking expertise from its telecommunications business into an edge that some say Nvidia has yet to match. The company is attempting to bundle hundreds of thousands of AI chips into massive clusters that function as a single computer to mimic cutting-edge silicon.

“They’ve managed to make up for the lack of access to great chips, critical inputs, by improving much more on their ecosystem efficiency,” Hong Kong University of Science and Technology economist Keyu Jin said at a recent Wall Street Journal event. “This is what China’s truly good at.”

An immediate bottleneck is output. Huawei’s planned production of its new chip—around 750,000 this year—will fall well short of demand. Huawei’s bundling strategy also means it needs several times as many chips to match the computing power of Nvidia’s systems. The company said it was working to increase supplies.

Beijing has encouraged chip companies, including Huawei, to license their workarounds and technology so that they could learn from each other, people familiar with the matter said.

Huawei unveiled its latest “fine-carving” alternative in May. Instead of trying to make transistors smaller, the company laid out a method for stacking circuits to cram more computing power into a single chip footprint. Huawei said that method would allow it to develop chips by 2031 that could outperform any semiconductor currently in production.

“This isn’t about Huawei overtaking the U.S. on a hairpin turn,” said Qingyuan Lin, a semiconductor analyst at Bernstein. “It’s more about finding a way to prevent the gap from widening quickly.”

To truly compete without reliance on foreign technology, China will have to build its own EUV machines, analysts say.

China is likely to figure out how to match the technology eventually, though it will take at least a decade and maybe as many as 50 years, according to Ray Wang, an analyst with research firm SemiAnalysis.

The difficulty lies in the technology’s combination of extreme complexity with extreme precision, said Chris Miller, a historian of technology at Tufts University and author of “Chip War.” In other words, the approach China used to build its first nuclear bomb may not be enough this time around.

“It’s a lot harder than nuclear weapons,” Miller said. “It’s orders and orders of magnitude more complex than almost every other type of manufacturing.”

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