Chinese tech giant Huawei has unveiled a safety-focused version of the artificial intelligence model DeepSeek, positioning the release as a major step in ensuring compliance with Beijing’s strict guidelines on how AI is deployed domestically.

The company claims the new model is “nearly 100% successful” in blocking politically sensitive discussions, reflecting how Chinese AI companies are increasingly required to integrate political safeguards directly into their systems.

Huawei announced the new model, DeepSeek-R1-Safe, on its official WeChat account late on Thursday. It said the system was trained using 1,000 of its in-house Ascend AI chips and co-developed with Zhejiang University, the alma mater of DeepSeek’s founder, Liang Wenfeng. Despite that link, Huawei stressed that neither DeepSeek itself nor Liang was directly involved in the project.

Building AI Within Beijing’s Red Lines

The model’s debut comes against the backdrop of China’s sweeping rules that require all AI models released for public use to conform to “socialist values” and avoid politically sensitive topics. Regulators have made clear that companies cannot launch consumer-facing AI products unless they pass rigorous reviews ensuring that chatbots and other AI tools do not produce responses that contradict Party messaging or touch on restricted subjects.

Huawei said DeepSeek-R1-Safe achieved “nearly 100% success” in filtering out harmful and politically sensitive content, including toxic speech, incitement to illegal activity, and politically restricted issues. However, in role-playing tests, disguised prompts, or encrypted coding scenarios, the success rate fell to 40%, highlighting the difficulty of ensuring airtight compliance.

Still, Huawei described the model as an advancement, reporting that it achieved an 83% comprehensive security defense capability in testing, outperforming rivals like Alibaba’s Qwen-235B and DeepSeek-R1-671B by 8% to 15% under identical conditions. Importantly, it suffered less than a 1% performance degradation compared to the original DeepSeek-R1, suggesting that stricter safety filters did not come at a significant cost to efficiency.

DeepSeek’s Role in China’s AI Strategy

The move also illustrates how the original DeepSeek models have become a backbone for China’s AI ecosystem. The company’s R1 and V3 releases earlier this year shook Silicon Valley and global investors, triggering a selloff of Western AI stocks due to their sophistication and efficiency. Since then, Chinese companies and universities have rushed to adopt, adapt, and localize DeepSeek’s architecture for a wide range of applications.

Huawei’s effort shows how those adaptations are increasingly being tied to political imperatives. Domestic AI chatbots already reflect Beijing’s priorities: Baidu’s Ernie Bot, China’s first large-scale answer to OpenAI’s ChatGPT, refuses to engage on politically sensitive subjects and redirects users toward neutral or Party-safe answers. Huawei’s new system takes this a step further, explicitly framing its compliance record as a feature in itself.

The announcement comes during Huawei Connect in Shanghai, the company’s flagship annual conference. Huawei also broke years of secrecy by unveiling roadmaps for chip and computing product development, underlining its ambitions to reduce reliance on foreign technology and stake a claim as a leader in both hardware and AI safety.

This dual emphasis — cutting-edge performance with ironclad compliance — has become a hallmark of how China’s AI champions are distinguishing themselves from Western rivals.

However, Huawei’s release underscores the dual challenge facing Chinese AI firms. On one side, they are under pressure to match the pace of Western leaders like OpenAI, Anthropic, and Google DeepMind in terms of innovation. On the other hand, they must operate within political guardrails that demand their systems actively defend against politically sensitive content.

This underlines how Beijing’s approach to the AI arms race encourages innovation, but only within strict ideological boundaries. Its guardrails on the overuse of DeepSeek, China’s most innovative AI model, are a clear sign that compliance and control are not secondary considerations but central pillars of how domestic AI will evolve.

Oracle is in talks with Meta Platforms for a cloud computing deal worth about $20 billion, in what could become one of the largest AI infrastructure agreements to date, a person familiar with the matter told Reuters on Friday.

If finalized, the multi-year deal would see Oracle provide Meta with computing power to train and deploy its fast-expanding artificial intelligence models. The arrangement would complement Meta’s existing partnerships with other cloud providers, reflecting the social media giant’s urgent push to secure faster and more reliable access to scarce computing resources.

Oracle has positioned itself as a key player in the AI infrastructure market by offering integrated cloud technologies and flexible deployment models. This positioning has enabled it to capture demand from some of the world’s most resource-hungry companies.

The prospective Meta deal comes just a week after the Wall Street Journal reported that OpenAI signed a contract with Oracle to purchase $300 billion worth of computing power over five years — one of the largest cloud deals ever recorded.

In recent months, Oracle has also struck partnerships with Amazon, Alphabet’s Google, and Microsoft, allowing their customers to run Oracle Cloud Infrastructure (OCI) alongside native services. Revenue from these arrangements surged more than sixteenfold in the first quarter, underlining how deeply entrenched Oracle has become in the new AI supply chain.

The enterprise software giant has not slowed its momentum. Just last week, it announced four multi-billion-dollar cloud contracts and said it expects several more in the coming months. It further projected that booked revenue at its OCI business would surpass half a trillion dollars.

The AI Arms Race for Computing Power

The negotiations with Meta highlight a broader industry shift, where computing power has become the single most valuable commodity in the AI arms race. Companies from OpenAI to Elon Musk’s xAI are aggressively securing long-term contracts with cloud providers to lock in access to chips, servers, and data center space capable of handling next-generation models.

For Meta, which has been expanding its AI ambitions across its platforms — from Llama models to generative AI features in Instagram and WhatsApp — ensuring uninterrupted compute supply is critical. Delays in access could blunt its ability to compete with rivals like OpenAI, Google DeepMind, and Anthropic.

Big Tech’s Cloud Strategies Diverge

Meta’s interest in Oracle adds another dimension to the competitive landscape of cloud alliances. Unlike Google, Microsoft, and Amazon, Meta does not operate a commercial cloud platform, forcing it to rely on external vendors for infrastructure.

By contrast, OpenAI has leaned heavily on Microsoft’s Azure while also diversifying with Oracle. Anthropic, meanwhile, has centered its compute strategy on Amazon Web Services, while Google continues to prioritize DeepMind’s needs within its own ecosystem.

For Oracle, which has long trailed Amazon, Microsoft, and Google in the public cloud market, these AI-driven mega-contracts are redefining its position. Oracle is rapidly carving out a role that could make it indispensable in the next wave of AI innovation by becoming the cloud provider of choice for companies desperate for large-scale compute.

Some analysts believe that if the Meta deal materializes, it would cement Oracle’s transformation from a legacy software vendor into a central force in global AI infrastructure. It would also underscore the sheer scale of spending underway, with tens and even hundreds of billions of dollars now being committed to ensure that the companies building the most powerful AI models have the computing backbone to support them.

The pending talks also raise questions about sustainability. It is believed that the unprecedented demand for data centers — and the energy required to power them — is creating bottlenecks in supply chains and raising concerns about environmental impact. Still, the race shows no sign of slowing, as securing compute is now seen as existential for AI players.

With Meta, OpenAI, and others turning to Oracle, the company has suddenly emerged as the unexpected kingmaker in the most expensive technology race of the decade.