China’s DeepSeek Just Dropped a New AI Model Built on Huawei Chips

2026-04-24 · Source: AutoGPT · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Emerging Technologies & Innovation · Depth: Intermediate, short

Summary

DeepSeek, a Chinese AI startup, released a preview of its next-generation open-source AI model, V4, on April 24, 2026. The model comes in two versions: V4-Pro with 1.6 trillion total parameters (49 billion active) and V4-Flash with 284 billion total parameters (13 billion active). Both support a one-million-token context window. A significant development is V4's design to run on domestic Chinese chips, specifically Huawei's Ascend 950 processors, supported by Huawei's "Supernode" technology, marking a shift from DeepSeek's previous reliance on Nvidia hardware. DeepSeek claims V4 leads all current open-source models in coding, math, and STEM benchmarks, and rivals closed-source systems from OpenAI, Google, and Anthropic in performance. V4 also features a "Hybrid Attention Architecture" that dramatically improves efficiency for long-context processing, reducing computing power by 73% and memory by 90% compared to V3.2 for one-million-token tasks.

Key takeaway

For AI Engineers and CTOs navigating U.S. export controls or seeking diverse hardware options, DeepSeek V4's successful deployment on Huawei Ascend 950 chips signals a viable alternative to Nvidia-dependent systems. Your teams should evaluate V4's open-source capabilities, especially its coding performance and long-context efficiency, as it could enable competitive AI development without reliance on restricted foreign hardware, potentially lowering costs and mitigating supply chain risks.

Key insights

DeepSeek's V4 model demonstrates high-performance AI can be developed using domestic Chinese hardware, challenging U.S. chip dominance.

Principles

• Open-source models can rival closed-source systems.
• Domestic chip ecosystems can support advanced AI training.

Method

DeepSeek V4 utilizes a "Hybrid Attention Architecture" to achieve significant efficiency gains in long-context processing, reducing computational and memory demands for large token windows.

In practice

• Integrate V4 for AI agent development due to strong coding.
• Explore V4 for long-context applications like document analysis.

Topics

• DeepSeek V4
• Huawei Ascend 950
• Open-source AI Models
• AI Agents
• U.S. Export Controls

Best for: AI Engineer, Investor, CTO, AI Scientist, Machine Learning Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by AutoGPT.