At the 2026 Huawei Connect conference in Shanghai, Huawei's rotating chairman Xu Zhijun delivered a message that would have sounded implausible three years earlier. The company's next-generation Ascend AI accelerators, he said, would be sold primarily in China. There was no capacity left for a broader international push.
"Even domestic demand for computing power is not yet fully met," Xu told reporters. Huawei would supply "a small number of products to some countries with particularly strong demand," but a full global rollout had no timeline.
The statement inverted the conventional narrative about China's AI chip industry. For years, the assumption in Western policy circles was that export restrictions would starve Chinese AI companies of advanced silicon, forcing them to either fall behind or depend on grey-market Nvidia hardware. Huawei's problem in September 2026 is not a shortage of demand. It is a shortage of supply.
The Price Signal
The clearest evidence of that imbalance is what Huawei is charging.
In September 2026, Huawei notified customers that the suggested price for its Ascend 950DT accelerator had risen roughly 60% over the previous three months, to 250,000 yuan (about $37,300) per card. That price was set in line with Nvidia's B200 — a benchmark Huawei had not previously attempted to match.
The increases were not confined to the flagship. The Ascend 950PR, which sold for approximately 60,000 yuan at the start of 2026, was fetching more than 80,000 yuan by September — a rise of about 30%. The older Ascend 910C board had climbed from roughly 90,000 yuan to above 110,000 yuan.
The cause is a memory shortage, not a pricing strategy. High-bandwidth memory (HBM), the vertically stacked memory chips that allow AI processors to access vast amounts of data at high speeds, accounts for a large share of an AI accelerator's production cost. The advanced HBM market is dominated by SK Hynix, Samsung, and Micron. Since December 2024, when Washington tightened controls on exports of certain advanced HBM products to China, Chinese chipmakers have relied increasingly on grey-market channels — paying several times what buyers outside China pay.
Huawei's sales representatives have told customers that HBM supply is "particularly limited" and pushing up costs. The company has said the Ascend 950 series will use two proprietary HBM technologies — HiBL 1.0 for the 950PR and HiZQ 2.0 for the 950DT — without detailing where or how the memory is manufactured.
The result is that Chinese AI chips are getting more expensive, not cheaper. The price hikes increase the cost of building AI computing capacity in China and highlight a growing bottleneck for domestic chipmakers.
The Supply Gap
Huawei's production constraints are structural.
The Ascend 910C is manufactured by SMIC using its second-generation 7-nanometer process, known as N+2. Yield rates improved from roughly 20% in September 2024 to approximately 40% — a significant gain, but still the ceiling on output. Each 910C integrates roughly 53 billion transistors and is assembled from two 910B dies via Chiplet packaging.
HBM supply is the tighter constraint. The 910C requires 128 GB of HBM, a component that has been subject to export restrictions since late 2024. Combined with 2.5D advanced packaging bottlenecks, monthly capacity ramp has been challenging. Industry estimates place it at a few thousand units per month, though figures vary depending on the counting method.
Huawei has set a full-year 2026 shipment target of 1.5 to 2 million Ascend dies across the product line, with about 600,000 of the flagship 910C. But the 910C alone shipped approximately 812,000 units in 2025, capturing nearly half of China's domestic market. In the first quarter of 2026, Huawei delivered another 150,000 cards, serving 37 leading large-model enterprises.
By August 2026, the inventory was gone. Procurement managers at several leading model companies were "pulling strings, adding budget, even prepaying" to secure a few thousand more Ascend 910C cards. The secondary market was pricing them at a 30% premium. ByteDance and Alibaba had cleared existing stock. Tencent, Baidu, and iFlytek were queuing for allocations.
One industry estimate suggested China's total advanced-node capacity at SMIC's N+2 line is about 2.6 million dies per year, against market demand of roughly 4.2 million.
The Customer Crunch
The supply shortage is not hypothetical for Huawei's customers. It is a planning constraint.
In April 2026, Reuters reported that ByteDance, Tencent, and Alibaba were all reaching out to Huawei about new chip orders following the launch of DeepSeek's V4 model. Customer testing of the new chip had gone well earlier in the year, with firms including ByteDance and Alibaba planning orders after samples were distributed in January.
Huawei has forecast its AI chip business revenue at approximately $12 billion in 2026, up from $7.5 billion in 2025 — growth of at least 60%. That forecast is based on orders already in hand. It assumes the capacity can be delivered.
The demand is not just about volume. It is about allocation. Huawei is prioritizing "the biggest Chinese tech companies and AI infrastructure builders" for deliveries of the Ascend 950DT. Smaller buyers are waiting.
The System-Level Response
Huawei's answer to the single-chip performance gap is architectural, not silicon-level.
The company has described its approach as "supernode plus cluster" — using system-level scale to compensate for individual chip limitations. The Ascend 910C supernode packs 384 chips into a single logical unit. The Ascend 950 supernode scales to 1,024 chips. The Ascend 960 generation is designed for 4,096 chips.
According to Huawei and third-party analysis, a 384-chip CloudMatrix 384 supernode delivers 1.7 times the BF16 performance of Nvidia's GB200 NVL72, with 3.6 times the memory capacity and 2.1 times the bandwidth, according to SemiAnalysis. SemiAnalysis calculated that the supernode architecture effectively erased the single-card disadvantage through stacking and high-speed interconnect.
The trade-off is power consumption. The CloudMatrix 384 reportedly consumes roughly four times the power of an NVL72 system, according to third-party analysis. Huawei Vice President Li Junfeng has argued that power is not the limiting factor in China — an assessment consistent with the country's cheap western electricity and the "East Data, West Computing" build-out.
The architectural philosophy differs from Nvidia's. Nvidia pursues single-chip performance through advanced process nodes. Huawei pursues system performance through interconnection.
The Roadmap Acceleration
Huawei is not waiting for the supply situation to resolve before pushing the roadmap forward.
At Huawei Connect, the company announced that the Ascend 960DT would arrive in Q1 2027, three quarters ahead of its original schedule, with doubled performance compared to the previous generation. The 960PR is slated for Q3 2027.
The 960 generation introduces the Peerium computing architecture, built on Huawei's UnifiedBus interconnect technology. The Atlas 950 SuperPoD and SuperCluster are the first systems based on it. Huawei says a single Atlas 950 SuperCluster can connect up to 256,000 accelerator cards.
There is a caveat. Analyst Rui Ma noted on X that Huawei had previously said the Atlas 960 SuperPoD would scale to 15,488 Ascend 960 chips, but the version announced at Huawei Connect supports only 4,096. The chip timeline accelerated. The system scale did not keep pace.
What Sanctions Actually Did
The export control strategy was built on a simple premise: if China cannot access advanced chips, it cannot build advanced AI. Three years into the tightening, the evidence suggests a different outcome.
Huawei's AI chip revenue is growing at 60% year over year. Its flagship accelerator is priced in line with Nvidia's B200. Its customers include every major Chinese internet company. Its roadmap is accelerating, not stalling.
The constraints are real. HBM supply is tight. SMIC's advanced-node capacity is the ceiling. Yields are improving but not solved. Huawei cannot meet domestic demand, let alone export.
But the sanctions did not stop Huawei from building AI chips. They stopped Huawei from building them cheaply. They forced the company to rely on grey-market memory, proprietary HBM alternatives, and architectural workarounds that consume more power but deliver comparable system-level performance. They created a shortage that Huawei is now managing through allocation and price increases.
The companies affected most directly are not in Washington. They are in Beijing, Shenzhen, and Hangzhou — the procurement managers calling in favors to get a few thousand more Ascend cards.
Huawei's next-generation AI chips are sold out before they ship. The demand is not the problem. The supply is.
Sources: EET China (September 24, 2026); Bloomberg via Yahoo Finance (September 10, 2026); C114 via Phoenix Tech (August 2026); Reuters via Yahoo Finance (September 10, 2026); Reuters via Khaleej Times (April 29, 2026); Toutiao Daily (May 1, 2026); TrendForce (September 17, 2026); EET China (September 20, 2026); SCMP (June 25, 2026); TMTPost (July 5, 2026).
Disclaimer
The information provided in this article is for general informational and educational purposes only. It does not constitute legal, financial, or professional advice. The author and publisher are not responsible for any actions taken based on the content of this article. Readers should consult qualified professionals for advice specific to their situation. All trademarks and references to third-party products, services, or organizations are the property of their respective owners. The performance data and benchmarks discussed are based on specific research studies and may not generalize to all use cases or environments. As of the publication date, the AI landscape continues to evolve rapidly, and readers should verify current information independently.
Limitations
This analysis is based on reporting and public data available as of the article date; figures may be revised as sources update.
Forecasts from third-party analysts can change with market conditions.
Cost and pricing examples are point-in-time estimates; actual rates vary.
Country and company comparisons rely on public reporting, not operational data.
This sector moves fast; timelines and deal terms may be updated later.
Company deals and regulatory rulings may evolve; verify current status.
AI infrastructure is changing quickly; claims can become outdated soon.
Sources
- EET China (September 24, 2026)
- Bloomberg via Yahoo Finance (September 10, 2026)
- C114 via Phoenix Tech (August 2026)
- Reuters via Yahoo Finance (September 10, 2026)
- Reuters via Khaleej Times (April 29, 2026)
- Toutiao Daily (May 1, 2026)
- TrendForce (September 17, 2026)
- EET China (September 20, 2026)
- SCMP (June 25, 2026)
- TMTPost (July 5, 2026).
The information provided in this article is for general informational and educational purposes only. It does not constitute legal, financial, or professional advice. The author and publisher are not responsible for any actions taken based on the content of this article. Readers should consult qualified professionals for advice specific to their situation. All trademarks and references to third-party products, services, or organizations are the property of their respective owners. The performance data and benchmarks discussed are based on specific research studies and may not generalize to all use cases or environments. As of the publication date, the AI landscape continues to evolve rapidly, and readers should verify current information independently.
Limitations: This analysis is based on reporting and public data available as of the article date; figures may be revised as sources update.; Forecasts from third-party analysts can change with market conditions.; Cost and pricing examples are point-in-time estimates; actual rates vary.; Country and company comparisons rely on public reporting, not operational data.; This sector moves fast; timelines and deal terms may be updated later.; Company deals and regulatory rulings may evolve; verify current status.; AI infrastructure is changing quickly; claims can become outdated soon.