Nvidia has agreed to acquire Hugging Face for $12.9 billion, in a major move that takes the chip giant deeper into the software and open-source side of artificial intelligence. But the deal did not begin with Nvidia knocking on Hugging Face’s door.&nbsp;Hugging Face CEO Clément Delangue told CNBC that his company approached Nvidia CEO Jensen Huang first. He said the discussions moved quickly and, just weeks later, the companies had agreed on a deal. Delangue said Hugging Face had reached a “turning point” and needed more resources, scale and visibility.&nbsp;<h2>Why Nvidia wants Hugging Face</h2>Hugging Face has become one of the biggest platforms for developers working with open-source AI models. Its platform lets researchers and developers share, discover and work with AI models, datasets and tools. Nvidia has already worked with Hugging Face, including integrating its DGX Cloud infrastructure with the platform to give developers access to AI supercomputing.&nbsp;The acquisition therefore gives Nvidia something that its GPUs alone cannot provide: a much deeper connection with the developers building AI models and applications. Nvidia said Hugging Face will remain an open platform for the wider AI ecosystem. Huang said the companies will work to scale its platform, strengthen its infrastructure and expand access to AI for developers and institutions worldwide.&nbsp;<h2>Nvidia is going far beyond chips</h2>The $12.9 billion deal shows how Nvidia’s ambitions are expanding. The company became the central hardware supplier behind the generative AI boom, but Huang has increasingly positioned Nvidia as a full AI computing platform rather than simply a chipmaker. Nvidia’s latest results show the scale of that business. It reported $96.2 billion in quarterly revenue, with data-centre revenue reaching $89 billion.&nbsp;Buying Hugging Face takes Nvidia further up the AI stack, closer to the models, developers and software that turn computing power into useful AI products.&nbsp;<h2>A major acquisition for Nvidia</h2>The Hugging Face purchase would rank among Nvidia’s largest acquisitions. The company’s strategy has increasingly involved partnerships and investments across the AI ecosystem, including model developers and infrastructure companies. For Hugging Face, meanwhile, Delangue said Nvidia was a “perfect home” for the company and its open-source community. The deal comes at an important moment for open AI models, as developers increasingly look beyond a small group of closed AI labs. Nvidia now wants to be part of that shift not just by supplying the chips, but by owning a major part of the platform where the next generation of AI developers builds.

Nvidia has agreed to acquire Hugging Face for $12.9 billion after Hugging Face CEO Clément Delangue approached Jensen Huang about a deal. The acquisition gives Nvidia a major open-source AI platform and expands its business beyond chips.

Nvidia has agreed to acquire Hugging Face for $12.9 billion, in a major move that takes the chip giant deeper into the software and open-source side of artificial intelligence. But the deal did not begin with Nvidia knocking on Hugging Face’s door. Hugging Face CEO Clément Delangue told CNBC that his company approached Nvidia CEO Jensen Huang first. He said the discussions moved quickly and, just weeks later, the companies had agreed on a deal. Delangue said Hugging Face had reached a “turning point” and needed more resources, scale and visibility. Why Nvidia wants Hugging Face Hugging Face has become one of the biggest platforms for developers working with open-source AI models. Its platform lets researchers and developers share, discover and work with AI models, datasets and tools. Nvidia has already worked with Hugging Face, including integrating its DGX Cloud infrastructure with the platform to give developers access to AI supercomputing. The acquisition therefore gives Nvidia something that its GPUs alone cannot provide: a much deeper connection with the developers building AI models and applications. Nvidia said Hugging Face will remain an open platform for the wider AI ecosystem. Huang said the companies will work to scale its platform, strengthen its infrastructure and expand access to AI for developers and institutions worldwide. Nvidia is going far beyond chips The $12.9 billion deal shows how Nvidia’s ambitions are expanding. The company became the central hardware supplier behind the generative AI boom, but Huang has increasingly positioned Nvidia as a full AI computing platform rather than simply a chipmaker. Nvidia’s latest results show the scale of that business. It reported $96.2 billion in quarterly revenue, with data-centre revenue reaching $89 billion. Buying Hugging Face takes Nvidia further up the AI stack, closer to the models, developers and software that turn computing power into useful AI products. A major acquisition for Nvidia The Hugging Face purchase would rank among Nvidia’s largest acquisitions. The company’s strategy has increasingly involved partnerships and investments across the AI ecosystem, including model developers and infrastructure companies. For Hugging Face, meanwhile, Delangue said Nvidia was a “perfect home” for the company and its open-source community. The deal comes at an important moment for open AI models, as developers increasingly look beyond a small group of closed AI labs. Nvidia now wants to be part of that shift not just by supplying the chips, but by owning a major part of the platform where the next generation of AI developers builds.

Nvidia has agreed to acquire Hugging Face for $12.9 billion after Hugging Face CEO Clément Delangue approached Jensen Huang about a deal. The acquisition gives Nvidia a major open-source AI platform and expands its business beyond chips.

Jensen Huang’s Nvidia makes a huge open-source AI bet with Hugging Face deal

Nvidia and other firms have raised AI chip prices as surging demand for artificial intelligence hardware pushes up memory costs in what is being described in the media as ‘RAMageddon’ or ‘RAMpocalypse’. Memory costs are now squeezing Indian IT firms, data-centre operators and electronics makers. A global shortage of DRAM or Dynamic Random-Access Memory and high-bandwidth memory (HBM) is deepening. The memory crisis that began in 2025 intensified in 2026. Memory prices rose sharply as chipmakers redirected capacity towards more profitable AI-related products.<h2>AI turns up the heat: Rise of HBM chips</h2>High-bandwidth memory (HBM) multi-stack chips are fast gaining ground over traditional RAM in AI systems. HBM is estimated to account for more than a fifth of DRAM wafer input among major suppliers. Producing the equivalent amount of HBM memory can require roughly three to four times the wafer capacity used for conventional DDR5 chips.Hyperscalers including Microsoft, Google, Amazon and Meta are securing large volumes of HBM and server DRAM for AI training and inference. Such long-term supply agreements and open-ended orders have led to a squeeze in memory availability.Memory makers like Samsung, SK Hynix and Micron have shifted capacity towards HBM and high-capacity server memory. These three companies together control about 95 per cent of the DRAM market. Their shift in priorities has left less capacity for PCs, smartphones, gaming consoles and conventional enterprise hardware.Also read: <a href="https://www.wionews.com/world/us-banned-its-best-chips-from-china-renting-them-is-still-legal-1787169656437">US banned its best chips from China. Renting them is still legal</a><h2>Prices are surging for memory</h2>Conventional DRAM contract prices jumped by about 90-98 per cent quarter-on-quarter in the first quarter of 2026. Overall DRAM and NAND prices have risen by 200-400 per cent in some segments since the shortage intensified.For instance, retail DDR5 memory kits that used to sell for about $80-250 in mid-2025 are now worth $300-650 or more. Server DRAM lead times have also exceeded 40 weeks.<a href="https://www.wionews.com/videos/chip-workers-gain-higher-pay-status-security-in-south-korea-1786083318916/embed">https://www.wionews.com/videos/chip-workers-gain-higher-pay-status-security-in-south-korea-1786083318916/embed</a><h2>The supply squeeze is unlikely to disappear quickly</h2>Chip fabrication plants can cost up to $20 billion and take years to reach full production. This is the reson why US firms are locking in supplies, signing multi-year contracts and passing on higher costs to consumers by raising prices.Besides Nvidia raising prices for AI chips, firms like Apple, Microsoft, Dell, Lenovo, HP and HPE have increased prices on their phones, computers, &nbsp;gaming consoles and servers by up to 15 per cent. Others that have recently raised prices include Asus and Cisco.&nbsp;Samsung, SK Hynix and Micron have also announced substantial increases for DRAM and HBM as they prioritise higher-margin products.<h2>Indian IT sector feels the squeeze of memory crisis</h2>Indian technology companies are facing the impact in the form of costlier hardware, data centres and infrastructure. They are trying to adjust to the situation with various strategies. For instance, Tech Mahindra avoided guaranteeing fixed memory and chip prices to customers. HCL Technologies is investing $350 million in data-centre capacity.The consumer market is feeling the pressure too. Smartphone shipments in India fell by about 10 per cent year-on-year in the second quarter of 2026. The sub-Rs 20,000 segment is particularly hit, due to the squeeze in hardware availability.&nbsp;Also read: <a href="https://www.wionews.com/world/anthropic-has-stacked-71-billion-in-chip-lease-debt-in-60-days-and-kept-it-off-its-books-1786631219409">Anthropic has stacked $71 billion in chip-lease debt in 60 days and kept it off its books</a>&nbsp;India is also trying to reduce its dependence on imported chips and chip components. The India Semiconductor Mission is backing further investment in semiconductors and memory-related infrastructure. Micron has begun commercial production at its assembly-and-test facility in Gujarat. &nbsp;Projected investment in India's data-centre ecosystem has crossed $200 billion.For Indian IT firms, the challenge is not limited to the price of a memory chip. The rising cost is hitting servers, data centres, smartphones and AI infrastructure as demand for computing capacity soars.

High demand for AI compute is causing a global crunch in memory. Chip costs are rising, which is leading to higher prices for all tech products, both software and hardware. Indian IT firms, data centres and electronics makers are tackling higher costs as supply tightens.

Nvidia and other firms have raised AI chip prices as surging demand for artificial intelligence hardware pushes up memory costs in what is being described in the media as ‘RAMageddon’ or ‘RAMpocalypse’. Memory costs are now squeezing Indian IT firms, data-centre operators and electronics makers. A global shortage of DRAM or Dynamic Random-Access Memory and high-bandwidth memory (HBM) is deepening. The memory crisis that began in 2025 intensified in 2026. Memory prices rose sharply as chipmakers redirected capacity towards more profitable AI-related products. AI turns up the heat: Rise of HBM chips High-bandwidth memory (HBM) multi-stack chips are fast gaining ground over traditional RAM in AI systems. HBM is estimated to account for more than a fifth of DRAM wafer input among major suppliers. Producing the equivalent amount of HBM memory can require roughly three to four times the wafer capacity used for conventional DDR5 chips. Hyperscalers including Microsoft, Google, Amazon and Meta are securing large volumes of HBM and server DRAM for AI training and inference. Such long-term supply agreements and open-ended orders have led to a squeeze in memory availability. Memory makers like Samsung, SK Hynix and Micron have shifted capacity towards HBM and high-capacity server memory. These three companies together control about 95 per cent of the DRAM market. Their shift in priorities has left less capacity for PCs, smartphones, gaming consoles and conventional enterprise hardware. Also read: US banned its best chips from China. Renting them is still legal Prices are surging for memory Conventional DRAM contract prices jumped by about 90-98 per cent quarter-on-quarter in the first quarter of 2026. Overall DRAM and NAND prices have risen by 200-400 per cent in some segments since the shortage intensified. For instance, retail DDR5 memory kits that used to sell for about $80-250 in mid-2025 are now worth $300-650 or more. Server DRAM lead times have also exceeded 40 weeks. https://www.wionews.com/videos/chip-workers-gain-higher-pay-status-security-in-south-korea-1786083318916/embed The supply squeeze is unlikely to disappear quickly Chip fabrication plants can cost up to $20 billion and take years to reach full production. This is the reson why US firms are locking in supplies, signing multi-year contracts and passing on higher costs to consumers by raising prices. Besides Nvidia raising prices for AI chips, firms like Apple, Microsoft, Dell, Lenovo, HP and HPE have increased prices on their phones, computers, gaming consoles and servers by up to 15 per cent. Others that have recently raised prices include Asus and Cisco. Samsung, SK Hynix and Micron have also announced substantial increases for DRAM and HBM as they prioritise higher-margin products. Indian IT sector feels the squeeze of memory crisis Indian technology companies are facing the impact in the form of costlier hardware, data centres and infrastructure. They are trying to adjust to the situation with various strategies. For instance, Tech Mahindra avoided guaranteeing fixed memory and chip prices to customers. HCL Technologies is investing $350 million in data-centre capacity. The consumer market is feeling the pressure too. Smartphone shipments in India fell by about 10 per cent year-on-year in the second quarter of 2026. The sub-Rs 20,000 segment is particularly hit, due to the squeeze in hardware availability. Also read: Anthropic has stacked $71 billion in chip-lease debt in 60 days and kept it off its books India is also trying to reduce its dependence on imported chips and chip components. The India Semiconductor Mission is backing further investment in semiconductors and memory-related infrastructure. Micron has begun commercial production at its assembly-and-test facility in Gujarat. Projected investment in India's data-centre ecosystem has crossed $200 billion. For Indian IT firms, the challenge is not limited to the price of a memory chip. The rising cost is hitting servers, data centres, smartphones and AI infrastructure as demand for computing capacity soars.

High demand for AI compute is causing a global crunch in memory. Chip costs are rising, which is leading to higher prices for all tech products, both software and hardware. Indian IT firms, data centres and electronics makers are tackling higher costs as supply tightens.

RAMageddon: Memory cost crisis squeezes IT firms as AI demand fuels global chip crunch

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Jensen Huang’s Nvidia makes a huge open-source AI bet with Hugging Face deal

RAMageddon: Memory cost squeezes IT firms as AI demand fuels global chip crunch