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The Nvidia Vera chip is rarely the headline when earnings beat estimates, but it should be. When Nvidia reported Q1 revenue of US$81.62 billion on Wednesday, beating analyst estimates of US$78.86 billion, and guided Q2 at US$91 billion–well above Wall Street’s US$86.84 billion forecast–the numbers did what Nvidia numbers always do: dominate the room. But […]
\nThe post Nvidia’s Vera chip is the US$200 billion bet Jensen Huang doesn’t want you to overlook appeared first on AI News.
", "content_html": "The Nvidia Vera chip is rarely the headline when earnings beat estimates, but it should be. When Nvidia reported Q1 revenue of US$81.62 billion on Wednesday, beating analyst estimates of US$78.86 billion, and guided Q2 at US$91 billion–well above Wall Street’s US$86.84 billion forecast–the numbers did what Nvidia numbers always do: dominate the room.
\n\n\n\nBut buried in CEO Jensen Huang’s conference call with analysts was something more strategically interesting than another quarterly beat. Huang told analysts that Nvidia’s new Vera central processors unlock access to a US$200 billion market, one that sits entirely outside the US$1 trillion the company has already forecast from its Blackwell and Rubin AI GPU lineup between 2025 and 2027.
\n\n\n\nHe expects Vera chip revenue to hit US$20 billion by the end of this fiscal year. “I expect (Vera) to be the second largest” sales contributor, Huang said during the call.
\n\n\n\nThat’s not a footnote. That’s a second front.
\n\n\n\nThe reason Nvidia needs a second front is straightforward: its biggest customers are building their own. Google, Amazon, and Microsoft–collectively expected to pour more than US$700 billion into AI infrastructure this year, up sharply from around US$400 billion in 2025, are simultaneously pouring funds into custom silicon to run AI models. Intel and AMD are also touting CPUs as a credible play for inference workloads.
\n\n\n\nThe narrative in the chip industry has shifted from who can train the biggest model to who can serve it cheapest and fastest. Inference is where Nvidia’s GPU dominance is most exposed. Training large models is still firmly Nvidia territory, but inference, generating answers at scale, in real time, is increasingly where custom chips from Google’s TPU line, Amazon’s Trainium and others are making their case.
\n\n\n\nNvidia’s answer is Vera. The chip, developed in part using technology from Groq, a startup specialising in inference that Nvidia licensed in a deal reportedly worth around US$17 billion, targets exactly this workload. The full Vera Rubin platform, which combines the Vera CPU with Rubin GPUs, is set to launch later this year.
\n\n\n\nHuang was candid about one problem: supply. “My sense is that we’ll be supply-constrained through the entire life of Vera Rubin,” he said on the call. It’s a telling admission for a product Nvidia is positioning as a major growth pillar. To get ahead of disruptions, Nvidia is spending heavily on the supply chain. The company disclosed that its supply commitments rose to US$119 billion in Q1, up from US$95.2 billion the previous quarter, a significant jump that reflects both confidence in demand and anxiety about a global memory chip crunch.
\n\n\n\nNvidia also announced a US$80 billion share repurchase programme and raised its quarterly cash dividend to 25 cents per share, from 1 cent, moves that signal financial confidence even as Huang warned of tightening supply.
\n\n\n\nDespite the beats, Nvidia shares fell 1.6% in extended trading after the results. eMarketer analyst Jacob Bourne captured the mood: “Nvidia delivered another beat, but at this point that’s essentially priced in as it keeps beating quarter after quarter. The lingering question is whether it can convince investors the AI buildout has durability into 2027 and 2028, especially as the narrative shifts toward inference workloads and competing silicon from Google, Amazon, AMD, and Intel.”
\n\n\n\nHuang pushed back with numbers of his own. He pointed to a growing sub-segment of AI-specific cloud customers whose spend is now roughly equal to the hyperscalers, but growing faster quarter-over-quarter. “We should be growing faster than hyperscale capex,” he said.
\n\n\n\nThe Vera chip is central to that argument. Whether the supply chain cooperates is a different question entirely.
\n\n\n\n(Image source: Nvidia’s Newsroom)
\n\n\n\nSee Also: The Nvidia H200 China deal survived the Trump-Xi summit–just not in the way anyone expected
\n\n\n\nWant to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and co-located with other leading technology events. Click here for more information.
\n\n\n\nAI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.
\nThe post Nvidia’s Vera chip is the US$200 billion bet Jensen Huang doesn’t want you to overlook appeared first on AI News.
", "content_text": "The Nvidia Vera chip is rarely the headline when earnings beat estimates, but it should be. When Nvidia reported Q1 revenue of US$81.62 billion on Wednesday, beating analyst estimates of US$78.86 billion, and guided Q2 at US$91 billion–well above Wall Street’s US$86.84 billion forecast–the numbers did what Nvidia numbers always do: dominate the room.\nBut buried in CEO Jensen Huang’s conference call with analysts was something more strategically interesting than another quarterly beat. Huang told analysts that Nvidia’s new Vera central processors unlock access to a US$200 billion market, one that sits entirely outside the US$1 trillion the company has already forecast from its Blackwell and Rubin AI GPU lineup between 2025 and 2027.\nHe expects Vera chip revenue to hit US$20 billion by the end of this fiscal year. “I expect (Vera) to be the second largest” sales contributor, Huang said during the call.\nThat’s not a footnote. That’s a second front.\nThe Vera chip and the inference pivot\nThe reason Nvidia needs a second front is straightforward: its biggest customers are building their own. Google, Amazon, and Microsoft–collectively expected to pour more than US$700 billion into AI infrastructure this year, up sharply from around US$400 billion in 2025, are simultaneously pouring funds into custom silicon to run AI models. Intel and AMD are also touting CPUs as a credible play for inference workloads.\nThe narrative in the chip industry has shifted from who can train the biggest model to who can serve it cheapest and fastest. Inference is where Nvidia’s GPU dominance is most exposed. Training large models is still firmly Nvidia territory, but inference, generating answers at scale, in real time, is increasingly where custom chips from Google’s TPU line, Amazon’s Trainium and others are making their case.\nNvidia’s\nanswer\nis Vera. The chip, developed in part using technology from Groq, a startup specialising in inference that Nvidia licensed in a deal reportedly worth around US$17 billion, targets exactly this workload. The full Vera Rubin platform, which combines the Vera CPU with Rubin GPUs, is set to launch later this year.\nSupply is already the constraint\nHuang was candid about one problem: supply. “My sense is that we’ll be supply-constrained through the entire life of Vera Rubin,” he said on the call. It’s a telling admission for a product Nvidia is positioning as a major growth pillar. To get ahead of disruptions, Nvidia is spending heavily on the supply chain. The company disclosed that its supply commitments rose to US$119 billion in Q1, up from US$95.2 billion the previous quarter, a significant jump that reflects both confidence in demand and anxiety about a global memory chip crunch.\nNvidia also announced a US$80 billion share repurchase programme and raised its quarterly cash dividend to 25 cents per share, from 1 cent, moves that signal financial confidence even as Huang warned of tightening supply.\nThe question investors are asking\nDespite the beats, Nvidia shares fell 1.6% in extended trading after the results. eMarketer analyst Jacob Bourne captured the mood: “Nvidia delivered another beat, but at this point that’s essentially priced in as it keeps beating quarter after quarter. The lingering question is whether it can convince investors the AI buildout has durability into 2027 and 2028, especially as the narrative shifts toward inference workloads and competing silicon from Google, Amazon, AMD, and Intel.”\nHuang pushed back with numbers of his own. He pointed to a growing sub-segment of AI-specific cloud customers whose spend is now roughly equal to the hyperscalers, but growing faster quarter-over-quarter. “We should be growing faster than hyperscale capex,” he said.\nThe Vera chip is central to that argument. Whether the supply chain cooperates is a different question entirely.\n(Image source:\nNvidia’s Newsroom\n)\nSee Also:\nThe Nvidia H200 China deal survived the Trump-Xi summit–just not in the way anyone expected\nWant to learn more about AI and big data from industry leaders?\nCheck out\nAI & Big Data Expo\ntaking place in Amsterdam, California, and London. The comprehensive event is part of\nTechEx\nand co-located with other leading technology events. Click\nhere\nfor more information.\nAI News is powered by\nTechForge Media\n. Explore other upcoming enterprise technology events and webinars\nhere\n.\nThe post\nNvidia’s Vera chip is the US$200 billion bet Jensen Huang doesn’t want you to overlook\nappeared first on\nAI News\n.", "image": { "url": "https://virtues.guru/tech-assets/13_Data_General_One_Laptop_Computer_Austin_Calhoon_Photograph.jpg", "file": "13_Data_General_One_Laptop_Computer_Austin_Calhoon_Photograph.jpg", "title": "File:Data General One Laptop Computer Austin Calhoon Photograph.jpg" }, "language": "en", "translations": { "pt": { "title": "O chip Vera da Nvidia é a aposta de US$200 bilhões que Jensen Huang não quer que você ignore.", "content_text": "O chip da Nvidia, o Vera, é uma aposta de 200 bilhões de dólares que o CEO, Jensen Huang, não quer que os investidores ignorem. O chip, desenvolvido em parte com tecnologia da Groq, tem como alvo cargas de trabalho de inferência e se espera que seja o segundo maior contribuinte de vendas. Os maiores clientes da Nvidia estão construindo seus próprios silícios personalizados, e a empresa precisa de uma segunda frente para se manter competitiva. No entanto, a oferta já é um fator limitante, e a Nvidia está investindo pesadamente na cadeia de suprimentos. Apesar de superar as estimativas de lucro, as ações da Nvidia caíram 1,6% nas negociações estendidas, com os investidores questionando a capacidade da empresa de convencê-los da durabilidade do desenvolvimento de IA.", "summary_en": "Nvidia's Vera chip is a $200 billion bet that CEO Jensen Huang doesn't want investors to overlook. The chip, developed in part with technology from Groq, targets inference workloads and is expected to be the second largest sales contributor. Nvidia's biggest customers are building their own custom silicon, and the company needs a second front to stay competitive. However, supply is already a constraint, and Nvidia is spending heavily on the supply chain. Despite beating earnings estimates, Nvidia shares fell 1.6% in extended trading, with investors questioning the company's ability to convince them of the AI buildout's durability.", "translated_at": "2026-05-22T06:22:18.542268+00:00", "model": "translategemma:4b", "summary_model": "llama3.1:8b", "source": "json_summary" } } }