In this era of comprehensive AI computing infrastructure rollout, the global semiconductor industry is shifting its focus toward AI chips. China’s market is forging its unique industrial upgrading path under the dual thrust of export controls and independent innovation. AI chip supply-demand imbalance, rapid growth in domestic market share, gradual improvement of software ecosystems, and the simultaneous boom in memory and optical chips together form the core development landscape of the current chip industry. Bernstein’s “2025 China AI Chip Industry Big Report: Assessing China’s AI Chip Supply and Demand” and Hunan University’s “2025 Domestic AI Chip Software Ecosystem White Paper” provide precise data support and trend judgments for industry development. This report references Bernstein’s “2025 China AI Chip Industry Big Report,” Hunan University’s “2025 Domestic AI Chip Software Ecosystem White Paper,” and the 100-plus chip industry research reports and data at the end of this article.

Sustained explosive growth in AI computing demand has kept China’s AI chip market at high prosperity, with overall demand reaching $39.5 billion in 2025. Even with NVIDIA’s H20 chip resuming sales to China, total annual market supply could only reach $37 billion, leaving a supply-demand gap of $2.5 billion—a significant narrowing from the originally projected $12.6 billion gap. US export controls have objectively created a development window for domestic chip manufacturers, pushing the market share of domestic AI chips from 17% in 2023 to a projected 55% by 2027. The industry logic is shifting from supply-constrained to demand-constrained. China’s AI accelerator market maintains strong growth, with a CAGR of 60% from 2023 to 2027, reaching $71 billion in 2027. The surge in demand from large model training and inference scenarios is the core driver. Chart data and PDF templates for Chart 1 (China AI Accelerator Market Size Trend) have been shared in the membership group.

The resumption of NVIDIA H20 chip sales is the key factor in narrowing the supply-demand gap. NVIDIA can complete $10.5 billion in H20 order deliveries from September to December 2025, and with the market contribution of the new B30 chip at $280 million, domestic computing power shortages are effectively alleviated. ByteDance, Alibaba, Tencent, and Baidu are the core purchasers of H20 chips, accounting for over 80% of total demand in 2024. H20 supply recovery will directly drive rapid AI business advancement for top internet companies. Chart data and PDF templates for Chart 2 (China AI Chip Supply-Demand Gap Narrowing) have been shared in the membership group.

The market share of domestic AI chips continues to climb, reaching 37% in 2025. Huawei Ascend, Cambricon, and Hygon Information form the first tier of domestic chip manufacturers, gradually capturing overseas market share through policy support and technological iteration. Chart data and PDF templates for Chart 3 (Domestic AI Chip Market Share Trend) have been shared in the membership group.

Domestic AI chip software ecosystems have formed a clear four-layer architecture system, including the framework adaptation layer, core tool layer, basic support layer, and management monitoring layer. These four layers work in efficient synergy based on hardware computing power. Huawei Ascend builds a full-stack software ecosystem through CANN + MindSpore, while Moore Threads MUSA and Cambricon NeuWare focus on CUDA compatibility and inference optimization respectively, forming differentiated ecosystem layouts. PDF templates for Chart 4 (Four-Layer Architecture of Domestic AI Chip Software Ecosystem) have been shared in the membership group.

From an ecosystem maturity perspective, NVIDIA’s CUDA has built extremely high industry barriers through a comprehensive developer system. Huawei Ascend’s CANN community leads among domestic players, while Cambricon, Hygon and other manufacturers’ software ecosystems are still in the cultivation stage. High software ecosystem adaptation costs remain the core obstacle to large-scale domestic chip deployment, with CUDA compatibility being the key lever for domestic manufacturers to break through the market. Chart data and PDF templates for Chart 5 (Mainstream AI Chip Software Ecosystem Radar) have been shared in the membership group. Interpretation: SMEs and AI companies should prioritize selecting domestic chip solutions with stronger compatibility to effectively reduce technology migration costs. Industrial capital can focus on the ecosystem adaptation tool sector to fill the industry toolchain gap.

Domestic AI chip manufacturers have formed four competitive tiers. Huawei Ascend, Cambricon, and Hygon Information constitute the first tier, while Matrix Labs and Moore Threads make up the second tier. Different manufacturers have significant differences in technical routes, application scenarios, and commercialization progress. Chart data and PDF templates for Chart 6 (Domestic GPU厂商 Revenue Comparison) have been shared in the membership group.

In terms of profitability progress, Hygon Information achieved full-year profitability as early as 2021, Cambricon turned profitable in Q4 2024, while Matrix Labs and Moore Threads are still in the early commercialization stage, expected to reach break-even around 2026–2027. High R&D investment and dependence on advanced process nodes are industry-wide challenges. Leading manufacturers break through profitability bottlenecks first by leveraging premium大客户 resources. Chart data and PDF templates for Chart 7 (Domestic GPU Break-Even Timeline) have been shared in the membership group.

Interpretation: SMEs should prioritize selecting mature domestically-produced chip products that have achieved commercial deployment to effectively reduce cooperation risks. Industrial capital should focus on manufacturers that have obtained大客户 validation and have clear profitability inflection points, avoiding risks in early R&D stages.

AI computing power demand has fundamentally reshaped the storage chip market structure, with the server segment surpassing consumer electronics to become the largest application scenario. By 2029, the server storage market will reach $145.8 billion, while AI edge-side storage leads all sub-sectors with a 36.4% CAGR. Chart data and PDF templates for Chart 8 (Storage Chip Downstream Application Market Size Growth) have been shared in the membership group. In 2026, the global storage chip market enters a boom phase, reaching $551.6 billion, a year-on-year increase of 134%, officially entering the super cycle defined by AI. Supply-demand mismatch between proactive production cuts by storage OEMs and explosive market demand has driven DDR4 prices up by 1800%, pushing the storage chip market into a seller’s market phase. Chart data and PDF templates for Chart 9 (Storage Chip Market Size & Growth Dual-Axis) have been shared in the membership group.

On the demand side, AI server storage demand grows at 50% growth rate, far ahead of traditional data centers, automotive electronics, and consumer electronics. HBM has become the core direction for storage chip technology iteration, with HBM4 product bandwidth expected to exceed 2TB/s. Chart data and PDF templates for Chart 10 (Storage Chip Demand Growth) have been shared in the membership group. On market structure, SK Hynix tops the DRAM market with its HBM product advantages at 38.2% market share, while Changxin Storage’s DRAM market share exceeds 5%. Yangtze Memory’s Xtacking architecture achieves 14% NAND market share. Domestic storage manufacturers achieve breakthroughs in both technological capability and market share. Chart data and PDF templates for Charts 12–13 (DRAM & NAND Market Structure Donut Charts) and Chart 5 (Storage Chip Domestic Breakthrough Timeline) have been shared in the membership group.

AI computing power explosion drives急剧 growth in 800G/1.6T optical module demand. EML chip capacity shortfall reaches 25%–30%, with orders booked through 2027 and beyond. Overseas manufacturers long monopolize the高端 optical chip market. Silicon photonics solutions achieve accelerated penetration, exceeding 50% market share in 2026. CW light sources become the main product for domestic substitution, with domestic manufacturers such as Yuanjie Technology and Shijia Photonics achieving mass shipment. Chart data and PDF templates for Chart 4 (Optical Chip Supply Chain Bottleneck & Silicon Photonics Substitution) have been shared in the membership group.

Chart data and PDF templates for Chart 16 (Optical Chip Market Structure & Supply-Demand Gap) and Chart 17 (CW Laser Growth Rate & Silicon Photonics Penetration) have been shared in the membership group. CW laser technology is the fastest-growing segment in the industry, with high-power products above 100mW achieving a CAGR of 276.2% from 2024 to 2030. The global optical chip market will reach $22.9 billion by 2030, nearly nine times the 2024 level.

Interpretation: SMEs can enter the sector by focusing on silicon photonics components and CW light source supporting links. Industrial capital should focus on domestic optical chip manufacturers to seize domestic substitution opportunities against the backdrop of capacity shortage.

The comparative analysis shows that Bernstein’s report core conclusions are a 2025 AI chip gap of $2.5 billion and 55% localization rate by 2027, based on actual shipment data from NVIDIA and AMD plus domestic manufacturer capacity calculations. The supply-demand gap forecast is precise and the localization rate prediction is clear. Hunan University’s white paper points out that the four-layer domestic ecosystem architecture has taken shape, with CUDA compatibility as the key, based on actual application scenarios of domestic manufacturers’ software stacks. The ecosystem layer division is clear and focuses on software adaptation pain points. The computing chip industry deep-dive report shows domestic GPU commercialization differentiation with Hygon and Cambricon leading, combining listed company public financial reports and channel survey data—厂商 revenue and profitability data are consistent with financial reports.

Actionable Checklist: SMEs should prioritize using mature domestic chips from Huawei Ascend and Hygon DCU, partnering with leading厂商 to reduce technology adaptation costs, and focus on inference scenarios for AI application deployment. Brand strategy leaders should layout AI computing infrastructure procurement, prioritizing dual-supply solutions locking in both NVIDIA H20 and domestic chips to avoid supply chain disruption risks. Industrial capital investment departments should focus on domestic memory chip and optical chip manufacturers, as well as the AI chip ecosystem adaptation tool sector, seizing the commercialization dividend of 2026–2027.

Risk Warnings & Mitigation Plans: Risk of US export control escalation may lead to continued restrictions on advanced processes and software ecosystems. Mitigation: pre-emptively layout mature process capacity, increase self-developed software ecosystem investment, and share domestic substitution supply chain resources within the community. Risk of industry overcapacity: the industry shifts to demand-constrained in 2027 with intensified price wars. Mitigation: focus on differentiated competition in niche scenarios, lock in long-term orders in advance, and connect downstream application demand resources within the community. Risk of technology iteration: global厂商 continuously upgrade technology, widening the domestic gap. Mitigation: increase R&D investment, focus on advantageous scenarios such as inference and edge computing, and coordinate industry-university-research resources within the community to advance technological breakthroughs.

Summary: China’s AI chip supply-demand gap narrowed to $2.5 billion in 2025, with NVIDIA H20 resuming supply alleviating short-term pressure, while long-term domestic substitution remains the core trend. Domestic AI chip market share will reach 55% by 2027, with software ecosystem and commercialization capability as the core competitiveness of manufacturers. Hygon, Cambricon, and Huawei Ascend lead the industry. The memory and optical chip sectors benefit from AI computing power explosion, with domestic manufacturers achieving breakthroughs in DRAM, NAND, and CW light sources, offering vast substitution potential. SMEs and industrial capital should focus on mature deployment scenarios, avoid overcapacity and technology iteration risks, and seize the golden window for domestic substitution. To obtain all report data at the end of this article, join the group chat and add our assistant WeChat: tecdat_cn.

Reference Reports (PDF) in This Topic

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