
How DeepSeek R1 may roil Nasdaq AI stocks right now
DeepSeek’s forthcoming R1 model is being framed as potentially competitive, a setup that could unsettle Nasdaq AI stocks in the near term. The central question is whether lower-cost, high-performing models compress expected returns across the AI supply chain.
Bridgewater Associates has argued the development could spark a short-term correction in U.S. tech, especially hardware-centric names, even if efficiency gains ultimately broaden industry adoption. That lens helps explain recent skittishness across AI-exposed equities and adjacent crypto assets.
What DeepSeek R1 is and its Nvidia Blackwell link
According to Reuters, DeepSeek’s latest model, expected as soon as next week, was trained on Nvidia’s Blackwell, the company’s most advanced AI chip series, despite U.S. restrictions on high-end exports. That ties R1 directly to the leading-edge GPU cycle at the heart of current AI capacity buildouts.
Competition claims arrive alongside IP controversy: as reported by Futurism, Anthropic has accused DeepSeek and other China-based firms of “distilling” its model. Verification of model performance and definitive GPU counts remain uncertain, which keeps scenario bands wide for investors.
Analysts broadly frame the disruption as a cost-curve story. “DeepSeek shows that it is possible to develop powerful AI models that cost less. It can potentially derail the investment case for the entire AI supply chain, which is driven by high spending from a small handful of hyperscalers,” said Vey-Sern Ling, Managing Director at Union Bancaire Privée.
Immediate impact: valuation pressure and AI capex reassessment
Valuation pressure may concentrate in chipmakers and enablers if premium hardware dependence eases. According to Markets Business Insider, DeepSeek’s cost profile has already raised questions about the need for U.S. firms to lean on the priciest accelerators, a risk relevant to Nvidia (NVDA), AMD (AMD), and Broadcom (AVGO).
Hyperscalers could reassess near-term AI capex intensity, procurement timing, and model pricing as unit economics evolve. If training and inference become cheaper, spend could tilt toward software, orchestration, and inference scale across Microsoft (MSFT), Alphabet (GOOGL), and Meta (META) rather than pure GPU counts.
At the time of this writing, Nvidia (NVDA) trades near $190.10 intraday, with a trailing P/E around 47, based on data from yahoo finance. These figures are contextual only and may be delayed.
Key signals to watch and scenario uncertainties
AI capex guidance and GPU mix: Blackwell versus H100 exposure
Investors should watch FY2026–FY2027 AI capex guidance and the mix between Blackwell and prior H100/H200 deployments. Alexandr Wang, CEO of Scale AI, has said DeepSeek may be using about 50,000 H100s, underscoring how mix shifts could affect demand timing and margins.
Regulatory and IP developments: export controls and distillation disputes
Export controls on advanced accelerators continue to shape access, costs, and deployment timelines for China-based training runs. The ongoing distillation dispute could influence IP enforcement, cross-licensing dynamics, and evaluation standards that determine permissible model commercialization.
FAQ about Nasdaq AI stocks
How could DeepSeek’s advances affect Nvidia, AMD, and Broadcom in the near term?
They may face valuation pressure if cheaper training and inference slow premium GPU demand, while a shift toward Blackwell could alter near-term revenue timing for NVDA, AMD, and AVGO.
Is the selloff in Nasdaq AI stocks a temporary correction or the start of a broader re-rating?
Evidence points to a correction with reassessment risk: near-term derating, then potential stabilization if efficiency expands adoption and capex shifts rather than collapses.
| DISCLAIMER: The information on this website is provided as general market commentary and does not constitute investment advice. We encourage you to do your own research before investing. |










