Nvidia’s grip on the AI chip market may be loosening—Huawei is stepping up. As the U.S. tightens export restrictions on cutting-edge AI hardware, Chinese tech firms are under increasing pressure to find domestic alternatives. At the forefront of this shift is Huawei, preparing to mass-ship its powerful new AI processor—the Ascend 910C GPU—as early as May 2025.
The timing couldn’t be more critical. With Nvidia’s H100 and H20 chips facing fresh regulatory hurdles, Huawei’s 910C is emerging as a promising alternative that could transform the AI development landscape in China. Designed to compete with Nvidia’s top-tier chips, the 910C represents both a technical and strategic milestone for China’s semiconductor ambitions.
In this article, we’ll explore what makes the Huawei 910C significant, how it stacks up against Nvidia’s offerings, the geopolitical forces accelerating its adoption, and what it means for the future of AI hardware globally.
What Is Huawei’s 910C AI Chip?
Overview & Core Specs
The Huawei Ascend 910C is the company’s latest high-performance AI chip, designed as a response to U.S. sanctions and the growing demand for domestic computing power in China. It serves as an evolution of the previous 910B model and is tailored for AI training and inference at scale. Key specs include:
- Double the computing power of the 910B
- Advanced AI workload support
- Optimized for large language models and deep learning
- Built on 7nm (N+2) process technology by SMIC (as reported)
Architectural Evolution from 910B
While not a complete redesign, the 910C represents an architectural upgrade from the 910B. Instead of focusing on novel architecture, Huawei enhanced integration and parallelism. This provides improved throughput, latency, and thermal efficiency—critical metrics in large-scale AI tasks.
Integration of Dual 910B Chips
The 910C essentially combines two 910B processors into one package using advanced chiplet-style packaging. This approach allows the chip to deliver:
- Increased compute density
- Greater parallel processing for transformer-based models
- Higher memory bandwidth, enabling smoother data flow
This dual-chip integration is what allows the 910C to rival Nvidia’s H100 in raw performance without needing completely new fabrication processes.
Memory, Power Efficiency, and Workload Optimization
The 910C features increased memory capacity, vital for LLMs and data-heavy inference tasks. Additionally, it includes power optimization techniques for more efficient performance-per-watt ratios. These factors make the 910C ideal for:
- AI inference at the edge or in data centers
- Training large models in secure domestic environments
- Handling multimodal AI workloads such as vision-language processing
By doubling down on efficiency and scale, Huawei’s 910C positions itself as China’s go-to AI chip in the post-Nvidia export era.
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910C vs H100
Huawei’s Ascend 910C and Nvidia’s H100 are both high-performance AI chips, but they approach computing from different perspectives:
| Feature | Huawei 910C | Nvidia H100 |
| Architecture | Dual 910B integration | Hopper (new architecture) |
| Manufacturing Node | 7nm (SMIC N+2, reportedly) | TSMC 4N |
| AI Training Capability | Competitive with H100 (on paper) | Industry gold standard |
| Ecosystem | MindSpore, Ascend SDK | CUDA, TensorRT, cuDNN (mature) |
| Availability | Domestic (China-centric) | Global (limited in China post-ban) |
While Nvidia’s H100 still leads globally in flexibility and ecosystem maturity, the 910C is engineered to close the gap within the Chinese AI ecosystem—especially now that H100/H20 availability is restricted due to U.S. sanctions.
Performance, Architecture, and Price
- Performance: Benchmarks are limited, but early insights suggest 910C offers similar or slightly lower training throughput compared to the H100, especially for transformer-based LLMs.
- Architecture: The 910C focuses on chiplet-based integration (dual 910Bs), while the H100 uses Nvidia’s brand-new Hopper architecture with proprietary enhancements like Transformer Engine.
- Price: Huawei is expected to price the 910C more competitively, offering a cost-efficient option for local AI firms without export license restrictions.
🇨🇳 Limitations & Potential Edge in Chinese Market
Limitations of 910C:
- Weaker global software ecosystem
- Less proven in real-world deployment compared to Nvidia
- Relies on domestic fabrication with lower chip yields (as per reports)
But here’s where it shines in China:
- No export restrictions, unlike Nvidia’s chips
- Government and enterprise adoption likely to increase
- Full compatibility with Chinese AI stacks (e.g., MindSpore)
- May become the default chip for LLM development and inference inside China
The Huawei 910C may not dethrone Nvidia globally, but within China, it’s poised to dominate, driven by necessity, political backing, and rapid scaling.
Why Now? U.S. Export Bans & Market Demand
Timeline of U.S. Restrictions on Nvidia (H100, B200, H20)
- 2022: U.S. bans Nvidia’s A100 and H100 chips from sale to China.
- 2023: New export rules limit Nvidia’s ability to sell advanced chips like B100 and H200.
- 2024–2025: Nvidia’s China-specific H20 chip also requires a license.
These restrictions have dramatically cut off China from cutting-edge AI hardware, creating a demand vacuum in the domestic market.
🇨🇳 How Chinese Firms Are Responding
- Increased investment in domestic GPU development (Huawei, Iluvatar CoreX, etc.)
- Accelerated AI hardware R&D pipelines
- Rapid scaling of data center infrastructure with local chips like 910B and 910C
- Use of open-source software ecosystems (e.g., MindSpore, PaddlePaddle) to bypass CUDA dependencies
Role of the Biden Administration in Reshaping the AI Chip Landscape
The Biden administration’s export controls are not just about trade—they are about geopolitical and military containment. These policies are reshaping global AI innovation zones, with China now investing in sovereign chip sovereignty like never before.
Inside the Manufacturing — Who’s Making the 910C?
SMIC and 7nm Process Details
- SMIC (Semiconductor Manufacturing International Corp.) is using its N+2 7nm process for key components.
- Despite sanctions, SMIC has achieved 7nm production, although with low yield rates, making scalability a concern.
Role of TSMC and Sophgo
- Some 910C chips may use semiconductors originally designed by TSMC for Sophgo, according to reports.
- This has triggered investigations by the U.S. Commerce Department.
- Huawei denies direct usage of TSMC-manufactured parts.
💰 Want to see where the money—and the future—is headed? Read how Elon Musk’s xAI startup just raised another $6BN and why it matters in the competition for AI dominance.Challenges in Yield, Production, and Legality
- Production challenges include yield inefficiencies, legal gray zones, and resource constraints.
- Potential legal exposure for firms collaborating with Huawei or using restricted nodes.
- Despite obstacles, Huawei is pushing forward due to strategic necessity.
Unique Features & Real-World Use Cases
Enhanced Support for Diverse AI Workloads
- Supports LLMs, computer vision, NLP, and real-time inference
- Optimized for parallel AI tasks and data throughput
Huawei AI Deployments in Data Centers, Research, and Inference
- Huawei is already deploying 910C in Atlas 800 servers
- Use cases include AI research institutes, enterprise AI stacks, and government inference centers
- Tightly integrated with Huawei’s MindSpore framework
Expert Quotes from Analysts
- Paul Triolo (Albright Stonebridge Group): “The 910C is likely to become the chip of choice for Chinese AI developers after the H20 restrictions.”
- RAND Researcher Lennart Heim: “TSMC chips were likely involved, making this a geopolitical as well as technical story.”
China’s Shifting AI Hardware Ecosystem
Role of Huawei, Moore Threads, Iluvatar CoreX
- Huawei leads in AI training chips
- Moore Threads focuses on GPU graphics and gaming AI
- Iluvatar CoreX offers AI accelerators optimized for LLMs
Alternatives Being Tested by Chinese AI Startups
- Companies are evaluating a mix of FPGA, custom ASICs, and low-power AI accelerators
- Some are even designing their own chips or using open-source RISC-V architectures for edge computing
What Global Investors and Researchers Are Watching
- Rise of domestic chip ecosystems in response to U.S. controls
- Potential for Chinese GPU exports to non-aligned nations
- Increasing divergence of AI development trajectories between U.S.-led and China-led blocs
FAQ’s
What is the Huawei 910C chip?
A: It’s an advanced AI GPU that combines two 910B processors, designed to rival Nvidia’s H100 in performance.
Is Huawei’s 910C better than Nvidia H100?
A: Performance is comparable in AI inference workloads, but it depends on use case and software optimization.
Why is China shifting from Nvidia to Huawei chips?
A: Due to U.S. export restrictions, Chinese companies are turning to domestic options like Huawei.
Is the 910C already shipping?
A: Yes, limited shipments have begun with mass rollout expected as early as May 2025.
Conclusion
Huawei’s 910C AI chip signals a major turning point in the global AI chip race. With Nvidia constrained in China, Huawei is rapidly positioning itself as a powerful alternative.
Bookmark this page to stay updated on Huawei 910C news and how it could shape the next generation of AI development in Asia and beyond.