Chinese AI Startups

DeepSeek’s valuation has more than doubled to above $20 billion in less than a week as Tencent and Alibaba enter funding discussions, signaling intensifying competition between U.S. and Chinese AI stacks at a moment when chip performance gaps remain wide but closing. For institutional crypto and blockchain investors, this mirrors broader geopolitical technology decoupling that could reshape compute infrastructure markets and alter which blockchain protocols and AI-native chains gain adoption in different regions.

• DeepSeek’s valuation jumped from $10 billion to above $20 billion within days as Tencent and Alibaba initiated investment talks.
• Nvidia CEO Jensen Huang warned that if DeepSeek optimizes AI models for Huawei chips instead of American hardware, it would be a “horrible outcome” for the U.S.
• Huawei’s Ascend 910C currently delivers only 60% of the inference performance of Nvidia’s H100, with American chips estimated to be 5x more powerful today but potentially 17x by 2027.

• $20B+ DeepSeek’s target valuation versus $10 billion floor announced Friday
• 60% Huawei Ascend 910C performance relative to Nvidia H100 benchmark
• 17x Projected U.S. chip performance advantage over Chinese rivals by 2027

DeepSeek’s valuation has surged past $20 billion in funding discussions with China’s largest tech firms, less than a week after the AI startup disclosed it was seeking at least $300 million at a $10 billion floor. Tencent Holdings and Alibaba Group are now in active talks to invest in the Chinese startup, according to reports on Wednesday citing four people familiar with the negotiations.

The rapid repricing reflects intensifying competitive pressure in AI infrastructure and a fundamental shift in how geopolitical technology competition plays out at the infrastructure layer, a concern with direct implications for how compute resources, and by extension blockchain networks, become distributed globally.

The speed of this valuation increase mirrors the broader urgency surrounding AI chip sovereignty. Within days of opening its first outside investor discussions, DeepSeek has attracted attention from two of China’s most valuable technology firms, each with incentives to reduce dependence on American semiconductor supply chains.

The talks remain ongoing, meaning the final valuation and funding amount could still shift, but the direction signals how quickly capital mobilizes around AI infrastructure bets perceived as strategically important to national technology ecosystems.

Nvidia CEO warns DeepSeek optimization for Huawei chips would harm U.S. competitiveness

Jensen Huang, Nvidia’s chief executive, articulated the core concern driving this funding competition during a Wednesday podcast appearance. He described it as a “horrible outcome” for the United States if DeepSeek’s AI models were optimized to run efficiently on Huawei chips rather than American processors.

Huang’s warning cuts to the heart of why institutional investors should track this funding round closely: the outcome determines whether future AI model development follows an American technology stack or a Chinese one, with cascading effects on which compute platforms, and which regional blockchain and protocol ecosystems, gain adoption in different markets.

If future AI models are optimised in a very different way than the American tech stack, and as AI diffuses out into the rest of the world with Chinese standards and technology, China will become superior to the United States.

Jensen Huang, Chief Executive, Nvidia

Huang framed the competition not as a near-term chip performance race, but as a standards-setting moment. Once large AI model developers optimize for a particular chip architecture, downstream applications, including blockchain infrastructure, AI-native protocols, and decentralized compute networks, tend to follow that same hardware assumption.

If DeepSeek V4 and future versions run optimally on Ascend silicon rather than H100s, that creates a self-reinforcing ecosystem where Chinese-standard hardware becomes the assumed baseline for global AI development, analogous to how x86 architecture became the assumed standard for decades of enterprise computing.

The strategic concern Huang raised extends beyond raw performance metrics. He noted that China possesses “abundant energy” for training and inference workloads and a “large pool of AI researchers,” meaning the country can overcome near-term chip deficits through scale and talent concentration.

DeepSeek’s own emergence as a credible alternative to OpenAI and Claude demonstrates this: the startup achieved competitive performance despite working under U.S. export controls on advanced semiconductors.

Huawei Ascend 910C delivers 60% of H100 performance but gap narrows as Chinese production scales

Current performance data suggests American chips still hold a decisive advantage. Huawei’s Ascend 910C, the chip preceding its newer 950PR model, delivers approximately 60% of the inference performance that Nvidia’s H100 achieves, a significant shortfall.

The H100 itself, however, is already two generations behind Nvidia’s current flagship processor, meaning the real-world gap between Huawei’s available silicon and Nvidia’s most advanced offerings is even wider.

The absolute performance spread remains substantial: American AI chips are estimated to be roughly five times more powerful than Chinese alternatives today.

However, that lead is projected to narrow considerably, with estimates suggesting American chips could hold only a 17-times performance advantage by 2027, a compression driven by both Chinese chip design improvements and anticipated slowdowns in American chipmaker gains as physical design limits tighten.

Production volume compounds the picture. Huawei is targeting 750,000 AI chip shipments in 2026, but that total production represents only 3% to 5% of the combined computing power Nvidia generates across all its customers. This means Chinese AI development remains fundamentally constrained by silicon availability, not just efficiency.

DeepSeek’s funding round therefore carries geopolitical weight precisely because capital flowing to the startup can accelerate model optimization techniques that extract maximum performance from scarce Huawei chips, reducing China’s dependence on incremental hardware improvements alone.

DeepSeek funding surge signals broader AI infrastructure competition reshaping compute markets

DeepSeek’s valuation jump coincides with a wider funding surge in AI infrastructure. Vast Data, a storage and compute company, announced a $1 billion funding round on the same day Huang made his remarks, indicating that capital markets are pricing in sustained competition for alternative AI stacks and infrastructure layers outside the dominant American ecosystem.

For institutional investors tracking blockchain and cryptocurrency infrastructure, this bifurcation matters directly.

If AI model training and inference optimizes around region-specific hardware stacks, blockchain protocols and decentralized compute networks will likely follow similar geographic and technical boundaries.

A Chinese-optimized AI stack built on Huawei chips creates natural incentives for blockchain protocols to optimize for deployment in that ecosystem, potentially fragmenting the global compute market into American-standard and Chinese-standard spheres.

Conversely, if Nvidia and American chipmakers maintain their advantage, the current concentration of AI infrastructure in U.S.-aligned jurisdictions will likely persist, benefiting blockchain platforms already embedded in that ecosystem.

The funding discussions involving Tencent and Alibaba also carry strategic weight because both firms operate blockchain or blockchain-adjacent platforms.

Tencent’s involvement in digital asset ecosystems and Alibaba’s blockchain infrastructure initiatives mean their investment in DeepSeek is not purely financial, but helps coordinate AI and blockchain infrastructure strategies at the firm level, accelerating the development of integrated Chinese technology stacks that reduce reliance on American components across multiple infrastructure layers.

The next decisive indicator is whether DeepSeek publicly discloses optimization metrics for Huawei Ascend chips versus Nvidia processors in model performance benchmarks. If inference latency and throughput on Ascend hardware approaches parity with H100 performance within the next two quarters, it signals that model optimization rather than raw chip performance is becoming the binding constraint on Chinese AI development, a turning point that would trigger accelerated adoption of Huawei chips by other Chinese AI firms and potentially force institutional investors to reprice both American chip export restrictions and regional blockchain infrastructure competition.