China's AI Compute Shift: Five Core Trends Emerge

Domestic AI compute adoption in China has reached a critical tipping point, marking an irreversible trend that reshapes the global semiconductor landscape. Recent analysis from Dongwu Securities identifies five core mainlines driving this transformation, signaling a strategic opportunity for local technology firms.

The report emphasizes that the era of policy-driven substitution is evolving into one of industrial self-validation. This shift suggests that Chinese hardware is no longer just a backup option but a competitive alternative capable of supporting advanced AI workloads.

Key Takeaways from the Report

• DeepSeek V4 Milestone: The model marks the first major use of domestic compute for training, proving technical viability.
• Five Industrial Pillars: GPU chips, CPU chips, Ascend ecosystem, compute leasing, and localized large models define the market.
• Infrastructure Completion: Domestic data centers have already exceeded '14th Five-Year Plan' targets ahead of schedule.
• Token Economy Revolution: Agent-driven economic models are creating new commercial value streams within the AI sector.
• Structural Value Split: By 2026, the industry will see a structural裂变 (fission) in commercial value distribution.
• Inference-First Strategy: Current adoption prioritizes inference tasks before moving to full-scale training capabilities.

The DeepSeek V4 Turning Point

The introduction of DeepSeek V4 represents a watershed moment for the Chinese AI industry. For the first time, a high-profile model utilized domestic computing power for its primary training phase. This achievement moves beyond theoretical capability to practical application.

Previously, reliance on imported GPUs from companies like NVIDIA dominated the sector. The successful deployment of local hardware demonstrates that the supply chain can support complex neural network training. This serves as a crucial proof point for other enterprises hesitant to switch ecosystems.

This development signals a transition from policy-driven mandates to market-led adoption. Companies are now choosing domestic solutions not solely due to regulatory pressure but because the technology has matured. It validates the years of investment in local semiconductor research and development.

Strategic Implications for Hardware

The ability to train large models locally reduces dependency on foreign supply chains. This autonomy is critical given ongoing geopolitical tensions and export controls. It ensures continuity in AI development regardless of external restrictions.

Furthermore, it encourages software developers to optimize their code for local architectures. As more models run on domestic chips, the software stack will become more robust and user-friendly. This creates a positive feedback loop for further innovation.

The Five Core Mainlines of AI Xinchuang

Dongwu Securities outlines five specific sectors that form the backbone of the emerging AI Xinchuang (information technology application innovation) industry. These areas cover the entire value chain from silicon to application.

1. GPU Chips: Local manufacturers are developing high-performance graphics processing units tailored for AI workloads. These chips aim to match the performance of international competitors while offering better integration with local systems.
2. CPU Chips: Central processing units remain vital for general computing tasks. Domestic CPU makers are focusing on improving multi-core efficiency and compatibility with existing enterprise software.
3. Ascend Industry Chain: Huawei’s Ascend series has emerged as a leading platform. The surrounding ecosystem, including cooling solutions and interconnect technologies, is rapidly expanding to support massive scale deployments.
4. Compute Leasing: A new business model where companies rent access to domestic supercomputing resources. This lowers the barrier to entry for startups and small businesses lacking capital for hardware purchases.
5. Xinchuang Large Models: Native AI models built specifically for the Chinese language and cultural context. These models leverage local data to provide superior accuracy in regional applications.

These five pillars create a comprehensive ecosystem. They ensure that every layer of the technology stack is secure, reliable, and domestically controlled.

Infrastructure Goals Exceeded Early

China’s domestic compute infrastructure has achieved remarkable progress. The nation has basically completed and even exceeded the goals set by the '14th Five-Year Plan'. This early success provides a strong foundation for future growth.

With physical infrastructure largely in place, the focus now shifts to optimization and utilization. Data centers are operational, and connectivity between nodes is improving. The challenge is no longer building capacity but filling it with efficient workloads.

Looking toward the '15th Five-Year Plan', the priorities will evolve. Core technology autonomy and continued infrastructure refinement will remain central themes. Policymakers and investors will likely concentrate on making these systems more energy-efficient and cost-effective.

Capital Allocation Trends

Capital expenditure in this sector is expected to remain high. Investors are pouring funds into companies that demonstrate genuine technological breakthroughs rather than just assembly operations. This selective funding promotes quality over quantity.

Banks and venture capital firms are aligning their portfolios with national strategic goals. This alignment ensures steady financial support for long-term projects that might otherwise struggle to secure funding in a volatile market.

Inference-Prioritized Adoption Strategy

The current phase of domestic compute adoption follows a distinct pattern. Inference-side implementation leads the charge, followed by gradual breakthroughs in training-side capabilities. Finally, ecosystem synergy binds these elements together.

Inference involves running trained models to generate outputs. It requires less computational power than training, making it easier to migrate to new hardware initially. Many enterprises are starting here to test stability and performance without risking critical R&D processes.

As confidence grows, companies will begin migrating training workloads to domestic platforms. This transition requires deeper optimization and more powerful hardware. However, the success of models like DeepSeek V4 proves this step is achievable.

Ecosystem synergy ensures that software tools, libraries, and developer communities adapt to the new environment. Without this support, hardware alone cannot sustain an industry. Collaborative efforts between chipmakers and software developers are essential for seamless integration.

What This Means for Global Tech

For Western technology leaders, this trend highlights the growing competitiveness of Asian markets. China is no longer just a consumer of AI technology but a creator of independent alternatives. This diversification could lead to a bifurcated global tech landscape.

Developers worldwide should monitor these developments closely. Understanding local architectures and optimization techniques may become valuable skills. Compatibility layers and cross-platform tools will gain importance as markets diverge.

Businesses operating in multiple regions must prepare for varied compliance and technical requirements. Dual-stack strategies might emerge, where companies maintain separate infrastructure for different geopolitical zones. This adds complexity but ensures resilience against supply chain disruptions.

Looking Ahead to 2026

By 2026, the AI industry is poised for a structural fission in commercial value. New revenue streams will emerge from agent-driven economies and specialized vertical models. The traditional cloud computing model may evolve to accommodate these decentralized, intelligent agents.

The token economy, driven by autonomous AI agents, will redefine how value is exchanged digitally. These agents will negotiate, transact, and collaborate independently, creating micro-economies within larger platforms.

Ultimately, the rise of domestic compute in China signifies a maturing global AI ecosystem. It demonstrates that technological sovereignty is achievable through sustained investment and strategic planning. Other nations may look to this model as they seek to reduce their own dependencies on foreign tech giants.