DeepSeek Launches V4 Model with Huawei Chip Integration, but Independent Benchmarks Show Mixed Performance Relative to Competitors
Introduction
On April 24, 2025, Chinese AI startup DeepSeek released a preview of its V4 model, the first to be adapted for Huawei's Ascend chips, marking a shift from its previous reliance on Nvidia hardware. Subsequent independent analysis, however, indicated that the model's performance, while improved, did not surpass all domestic and international rivals.
Main Body
**Model Launch and Hardware Collaboration** DeepSeek, the Beijing-based firm that gained global attention in early 2025 for its low-cost AI models, unveiled the V4 Pro preview on April 24. The company stated that the Pro version outperformed other open-source models on world-knowledge benchmarks, trailing only Google's closed-source Gemini-Pro-3.1. A notable aspect of the launch was the close collaboration with Huawei; the Chinese telecommunications firm confirmed that its Ascend chips were used in parts of the V4's training process. This pivot from Nvidia's AI chips underscores a broader trend in China's semiconductor sector, where domestic alternatives are being prioritized amid US export controls. Nvidia CEO Jensen Huang had previously warned that such a shift could harm the US company's developer ecosystem in China. The V4 model also includes a lower-cost Flash version, and DeepSeek indicated that the preview phase would allow for real-world feedback before a final release, for which no timeline was provided. **Independent Performance Assessments** Shortly after the launch, the benchmarking firm Artificial Analysis released an evaluation on April 25 (Friday) that placed the V4 Pro second among open-source models, behind Moonshot AI's Kimi K2.6. On the Artificial Analysis Intelligence Index, V4 Pro scored 52, compared to Kimi K2.6's 54. Leading closed-source US models—OpenAI's GPT-5.5, Anthropic's Claude Opus, and Google's Gemini 3.1 Pro—scored 60, 57, and 57, respectively. While the V4 Pro represented a clear improvement over its predecessor V3.2, it did not match the top-tier closed-source systems. AI engineer Daniel Dewhurst, who tested the V4 after its release, cautioned that the benchmark headlines should be treated with caution until independent evaluations and broader developer testing are conducted. He noted, however, that the V4 demonstrated that open models are narrowing the gap with closed models, particularly in cost efficiency, long-context handling, and coding tasks. The model can process over one million tokens, comparable to the context windows of OpenAI's GPT-5.4 and Anthropic's Claude Opus 4.6, but at a fraction of the computational cost. Limitations include a lack of support for multiple modalities such as images and video. **Geopolitical and Market Context** The launch occurred one day after the White House accused China of large-scale theft of US AI intellectual property, and ahead of a planned visit by US President Donald Trump to Beijing in May. DeepSeek has faced criticism from Washington and US rivals for allegedly relying improperly on American know-how; the company has acknowledged using Nvidia chips but has not clarified whether those chips were subject to export bans, and it has denied intentionally using synthetic data from OpenAI. The Trump administration approved the sale of Nvidia's H200 chips to China in January, but shipments have reportedly been delayed due to disagreements over sales terms in both countries. In financial markets, Chinese chipmakers Huahong Semiconductor and SMIC saw their shares rise 15% and 10%, respectively, on expectations of increased domestic chip adoption. Nvidia's shares also rose, partly due to Intel's positive revenue forecast, which reinforced confidence in sustained AI growth. DeepSeek's own valuation is reported to exceed US$20 billion, with tech giants Alibaba and Tencent reportedly in discussions to take stakes. The V4's release caused shares of domestic rivals Zhipu AI and MiniMax to decline by 9% each. **Differing Perspectives on Performance** While DeepSeek's initial announcement claimed top-tier open-source performance, the subsequent independent analysis by Artificial Analysis presented a more nuanced picture. The discrepancy may reflect differences in benchmark methodologies or the timing of evaluations. DeepSeek emphasized that the V4 is particularly suited for AI agent tasks, which require more computing power than standard chatbots. The model quickly rose to the top spot on Hugging Face, a popular developer platform, according to machine learning engineer Lewis Tunstall. He noted that the V4 excels at handling extremely long and complex text tasks at a lower cost than competing top models. Despite these strengths, the model's inability to process multiple modalities and its reliance on a single benchmark claim have led analysts to call for further independent verification.
Conclusion
DeepSeek's V4 model represents a significant technical step forward and a strategic shift toward domestic hardware, but its performance relative to both domestic and US rivals remains contested. The launch highlights China's progress in AI self-sufficiency amid geopolitical tensions, though the model's ultimate success will depend on independent validation and real-world adoption.