{"id":40896,"date":"2026-02-04T17:06:50","date_gmt":"2026-02-04T09:06:50","guid":{"rendered":"https:\/\/www.vtmarkets.com\/?p=40896"},"modified":"2026-02-04T17:06:50","modified_gmt":"2026-02-04T09:06:50","slug":"is-the-nvidia-bubble-about-to-pop","status":"publish","type":"post","link":"https:\/\/www.vtmarkets.com\/en-asia\/featured\/is-the-nvidia-bubble-about-to-pop\/","title":{"rendered":"Is the NVIDIA Bubble About to Pop?"},"content":{"rendered":"\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"559\" src=\"https:\/\/www.vtmarkets.com\/en-asia\/wp-content\/uploads\/sites\/27\/2026\/03\/ray_yang_banner_mobile-1024x559.png\" alt=\"\" class=\"wp-image-38001\"\/><\/figure>\n\n\n\n<p>Every major surge in technology markets eventually raises the same uncomfortable question: has enthusiasm run ahead of fundamentals?<\/p>\n\n\n\n<p>The rapid rise of artificial intelligence has propelled Nvidia into the centre of global markets, turning its chips into critical infrastructure for the AI economy. As a result, Nvidia\u2019s valuation has become highly sensitive to any development that challenges the assumption that more intelligence always requires more hardware.<\/p>\n\n\n\n<p>DeepSeek represents one such challenge.<\/p>\n\n\n\n<p>Rather than signalling the end of AI-driven growth, DeepSeek\u2019s breakthroughs force markets to confront a more nuanced risk: not demand destruction, but a potential repricing of expectations around margins, pricing power, and long-term hardware dependency.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">DeepSeek\u2019s Breakthrough: Efficiency Under Constraint<\/h2>\n\n\n\n<p>DeepSeek first caught global attention with the release of its V3 model, which demonstrated that frontier-level performance could be achieved under tight compute constraints.<\/p>\n\n\n\n<p>The model reportedly contained 671 billion parameters, yet only around 37 billion parameters were active at any given time. This sparse activation approach reduced real-time computational requirements to roughly one-eighteenth of what traditional large-scale models demand.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-rich is-provider-twitter wp-block-embed-twitter\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"twitter-tweet\" data-width=\"500\" data-dnt=\"true\"><p lang=\"en\" dir=\"ltr\">DeepSeek founder Liang Wenfeng\u2019s quantitative hedge fund generated returns of more than 50% last year <a href=\"https:\/\/t.co\/7epM5Ysrq5\">https:\/\/t.co\/7epM5Ysrq5<\/a><\/p>&mdash; Bloomberg (@business) <a href=\"https:\/\/twitter.com\/business\/status\/2010632000382636056?ref_src=twsrc%5Etfw\">January 12, 2026<\/a><\/blockquote><script async src=\"https:\/\/platform.twitter.com\/widgets.js\" charset=\"utf-8\"><\/script>\n<\/div><\/figure>\n\n\n\n<p>In addition, DeepSeek introduced its Mixture of Latent Attention (MLA) architecture, which significantly reduced memory usage \u2014 in some cases by up to 90% \u2014 allowing the same GPUs to handle far larger workloads.<\/p>\n\n\n\n<p>These design choices reframed a core assumption in the AI arms race: that scaling intelligence requires proportionally scaling hardware. Instead, DeepSeek demonstrated that software architecture could offset hardware limitations.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">From Model Release to Market Shock<\/h2>\n\n\n\n<p>The market impact of this efficiency breakthrough was immediate and severe. Nvidia experienced its largest single-day decline on record, with shares falling roughly 17% in one session, wiping out close to US$600 billion in market capitalisation.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-rich is-provider-twitter wp-block-embed-twitter\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"twitter-tweet\" data-width=\"500\" data-dnt=\"true\"><p lang=\"en\" dir=\"ltr\">&quot;DeepSeek really gave this incredible innovation to the world in terms of model efficiency by open-sourcing their V3 and their R1 models,&quot; T. Rowe Price&#39;s Dom Rizzo says. \u201cAI has the potential to be the biggest productivity enhancer for the global economy since electricity.\u201d <a href=\"https:\/\/t.co\/AM0xnGfTRO\">pic.twitter.com\/AM0xnGfTRO<\/a><\/p>&mdash; Yahoo Finance (@YahooFinance) <a href=\"https:\/\/twitter.com\/YahooFinance\/status\/1884250339576037550?ref_src=twsrc%5Etfw\">January 28, 2025<\/a><\/blockquote><script async src=\"https:\/\/platform.twitter.com\/widgets.js\" charset=\"utf-8\"><\/script>\n<\/div><\/figure>\n\n\n\n<p>This reaction was less about DeepSeek alone and more about surprise. Markets had been positioned for an AI future defined by ever-increasing GPU demand. The sudden appearance of a credible alternative path, one that delivered performance with far less compute \u2014 forced a rapid reassessment.<\/p>\n\n\n\n<p>Crucially, such shocks tend to diminish over time. Once a new efficiency frontier is recognised, future developments are more likely to result in repricing rather than panic-driven sell-offs.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why Efficiency Matters for Nvidia\u2019s Valuation<\/h2>\n\n\n\n<p>At first glance, efficiency-led AI innovation appears bearish for hardware leaders. If models require fewer GPUs, logic suggests demand should weaken.<\/p>\n\n\n\n<p>In reality, the implications are more complex.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Training Versus Inference<\/h3>\n\n\n\n<p>The most advanced AI training continues to rely on cutting-edge hardware. Efficiency gains primarily affect inference, where models are deployed at scale and cost sensitivity is highest. This distinction is critical: DeepSeek-style optimisation challenges margins and pricing power, not the relevance of high-end chips for frontier research.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Pricing Power Under Pressure<\/h3>\n\n\n\n<p>As efficiency improves and alternatives emerge, especially in price-sensitive markets, Nvidia\u2019s ability to dictate pricing weakens. The risk here is not collapsing revenue, but slower margin expansion than markets may currently assume.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Geopolitics and the Two-Track AI Ecosystem<\/h2>\n\n\n\n<p>Geopolitical constraints have accelerated efficiency-driven innovation. Restrictions on advanced chip exports forced Chinese firms to maximise performance within limited hardware access.<\/p>\n\n\n\n<p>Despite these constraints, the highest tiers of AI development still require Nvidia\u2019s technology. Partial easing of export restrictions allowed select high-end chips to enter China, albeit with additional costs and regulatory hurdles.<\/p>\n\n\n\n<p>This has created a paradoxical outcome: Nvidia\u2019s fastest-growing customers increasingly include firms actively developing software and hardware ecosystems designed to reduce long-term dependence on Nvidia itself.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">China\u2019s Domestic Challenge to Nvidia\u2019s Pricing Power<\/h2>\n\n\n\n<p>While Nvidia retains leadership in peak performance, domestic alternatives are no longer negligible.<\/p>\n\n\n\n<p>Huawei\u2019s Ascend 910C processor has emerged as a credible option for large-scale inference. By 2026, benchmark testing suggested that its performance in certain inference workloads could approach that of Nvidia\u2019s H200 derivatives.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-rich is-provider-twitter wp-block-embed-twitter\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"twitter-tweet\" data-width=\"500\" data-dnt=\"true\"><p lang=\"en\" dir=\"ltr\">Exclusive: China conditionally approves DeepSeek to buy Nvidia&#39;s H200 chips\u00a0 &#8211; sources <a href=\"https:\/\/t.co\/md8fHczhx8\">https:\/\/t.co\/md8fHczhx8<\/a> <a href=\"https:\/\/t.co\/md8fHczhx8\">https:\/\/t.co\/md8fHczhx8<\/a> <a href=\"https:\/\/t.co\/HXQRIh7d9h\">pic.twitter.com\/HXQRIh7d9h<\/a><\/p>&mdash; Reuters (@Reuters) <a href=\"https:\/\/twitter.com\/Reuters\/status\/2017152090846486725?ref_src=twsrc%5Etfw\">January 30, 2026<\/a><\/blockquote><script async src=\"https:\/\/platform.twitter.com\/widgets.js\" charset=\"utf-8\"><\/script>\n<\/div><\/figure>\n\n\n\n<p>At the same time, a group of leading Chinese AI firms \u2014 often referred to as the \u201cSix Tigers\u201d \u2014 have been optimising models specifically for domestic hardware ecosystems rather than Nvidia\u2019s CUDA stack.<\/p>\n\n\n\n<p>The result is not immediate displacement, but a structural ceiling on pricing power. Where viable alternatives exist, customers gain leverage.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Is This an AI Bubble?<\/h2>\n\n\n\n<p>Concerns about an AI bubble frequently draw comparisons to the early-2000s dot-com crash. However, the underlying fundamentals differ materially.<\/p>\n\n\n\n<p>At the height of the dot-com bubble, companies such as Cisco traded at 100\u2013200 times earnings, with operating margins in the 15\u201318% range. When capital dried up, valuations collapsed.<\/p>\n\n\n\n<p>By contrast, Nvidia\u2019s valuation sits closer to 45\u201346 times earnings, supported by net margins exceeding 50% and revenue approaching US$370 billion annually \u2014 nearly twenty times Cisco\u2019s peak revenue in 2000.<\/p>\n\n\n\n<p>AI spending today is increasingly tied to real monetisation across advertising, enterprise software, automation, and infrastructure, rather than speculative future demand.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What Traders Need to Know<\/h2>\n\n\n\n<p>For traders, developments like DeepSeek should be viewed as volatility catalysts with cross-asset implications, rather than single-stock events.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">1. Markets Move on Expectation Gaps<\/h3>\n\n\n\n<p>Price reactions are driven less by innovation itself and more by how new information challenges existing assumptions. Efficiency breakthroughs matter when they force markets to rethink future costs and margins.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. Risk Sentiment Transmits Faster Than Earnings<\/h3>\n\n\n\n<p>Shifts in AI narratives influence broader risk appetite. Foreign exchange and commodities often respond before equity fundamentals are formally repriced.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3. Volatility Is the Tradeable Outcome<\/h3>\n\n\n\n<p>AI-related news typically produces volatility clusters rather than clean directional trends, favouring tactical positioning across FX, indices, and gold.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4. Repricing Does Not Mean Collapse<\/h3>\n\n\n\n<p>The dominant risk is multiple compression, not revenue collapse. Understanding this distinction helps traders avoid overreacting to headlines while positioning for volatility.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">So, Is the NVIDIA Bubble About to Pop?<\/h2>\n\n\n\n<p>The evidence suggests this is not a classic bubble poised to burst, but a market undergoing repricing.<\/p>\n\n\n\n<p>DeepSeek challenges a key assumption underpinning Nvidia\u2019s valuation: that AI progress requires ever-increasing hardware intensity. When that assumption weakens, markets reassess margins, pricing power, and long-term growth trajectories.<\/p>\n\n\n\n<p>This reassessment can trigger sharp volatility and multiple compression without undermining the structural demand for AI. The risk lies in expectations resetting, not in AI demand disappearing.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Final Thoughts<\/h2>\n\n\n\n<p>DeepSeek is not an isolated disruptor, but a signal of AI\u2019s next competitive phase.<\/p>\n\n\n\n<p>As efficiency becomes as important as scale, markets will continue to re-evaluate where value truly sits across hardware, software, and infrastructure. For traders, this ongoing reassessment ensures that AI remains not just a growth story, but a persistent source of volatility.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Every major surge in technology markets eventually raises the same uncomfortable question: has enthusiasm run ahead of fundamentals?<\/p>\n","protected":false},"author":64,"featured_media":38001,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":true,"footnotes":""},"categories":[25,28],"tags":[29],"class_list":["post-40896","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-featured","category-learn","tag-learn"],"acf":{"acf_article_selection_author":{"value":"ray-yang","label":"Ray Yang"}},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/posts\/40896","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/users\/64"}],"replies":[{"embeddable":true,"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/comments?post=40896"}],"version-history":[{"count":0,"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/posts\/40896\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/media\/38001"}],"wp:attachment":[{"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/media?parent=40896"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/categories?post=40896"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.vtmarkets.com\/en-asia\/wp-json\/wp\/v2\/tags?post=40896"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}