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Nvidia plans new chip to speed AI processing: WSJ - The Economic Times
Nvidia plans to launch a new processor to help OpenAI and other clients run AI systems faster and more efficiently. The chip is for "inference" computing and will debut at Nvidia's GTC conference. It incorporates a design by startup Groq.Nvidia plans to launch a new processor designed to help OpenAI and other customers build faster, more efficient AI systems, the Wall Street Journal reported on Friday, citing people familiar with the matter. Nvidia is developing a new system for "inference" computing, a ā form ā of processing that allows AI models to respond to queries, the report said. The new platform is set to be unveiled at Nvidia's GTC developer conference in San Jose next month and will incorporate a chip designed by startup Groq, the report added citing people familiar. Reuters could not immediately verify ā the report. Nvidia and OpenAI did not immediately respond to Reuters request for comment. Reuters earlier this month reported OpenAI ā is unsatisfied with the speed at which Nvidia's hardware can spit out answers to ChatGPT users for specific types of problems such as software development and AI communicating with other software. It needs new hardware that would eventually provide about 10% of OpenAI's inference computing needs in the future, one of the sources told Reuters. The ChatGPT maker has discussed working with startups including Cerebras and Groq to provide chips for faster inference, two sources said. But Nvidia ā struck a $20-billion licensing deal with Groq that shut down OpenAI's talks, one of the sources told Reuters. In September, Nvidia said it intended to pour as much as $100 billion into OpenAI as part of a deal that gave the chipmaker a stake in the startup and gave OpenAI the cash it needed to buy the advanced chips.
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OpenAI Is Set to Be the Biggest Customer for the Upcoming NVIDIA-Groq AI Chip, Allocating 3GW of Dedicated 'Inference Capacity'
OpenAI's newest partnership with NVIDIA not only focuses on Vera Rubin but also on inference capacity, which will be provided by the upcoming NVIDIA-Groq solution. OpenAI is currently engaged in financing deals with infrastructure partners all across the AI industry, and the AI giant recently announced $110 billion in fresh capital, driven by the likes of NVIDIA, SoftBank, and Amazon. OpenAI calls the investments a necessity to keep the AI bandwagon up and running, and they have been one of the ways the firm has secured the computing power it needs. A WSJ report reveals that NVIDIA will showcase its Groq-focused "processor" at this year's GTC 2026, in line with our previous reporting. More specifically, OpenAI will be the biggest customer of the upcoming solution, which is an interesting decision. In the recent commitment by NVIDIA into OpenAI, it was revealed that the latter will use 3GW of "dedicated inference capacity", likely coming from what NVIDIA will showcase in March. Earlier reports have suggested that inference is a major concern for OpenAI in recent times, and that the company had been 'displeased' with what NVIDIA had been offering to address inference. OpenAI has agreed to become one of the largest customers of the new processor, some of the people said, representing a major win for Nvidia. The ChatGPT maker, which is one of Nvidia's largest customers, has spent the past few months shopping for more efficient alternatives to Nvidia's chips. - WSJ OpenAI was reported to be in talks with Cerebras and Groq as well to enter into agreements focused on providing optimal performance for latency-sensitive workloads. But now, it appears that OpenAI is sticking with NVIDIA, likely indicating that the upcoming solution built around Groq's LPUs is promising enough for the AI giant to commit to 3GW of capacity. Regarding what we expect from the NVIDIA-Groq arrangement, the most likely solution is a hybrid compute tray configuration, as discussed here. For now, we expect major announcements from NVIDIA at this year's GTC, focusing on Vera Rubin, possibly next-gen Feynman, and the solution built around Groq.
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NVIDIA's GTC 2026 Reveal: AI Processor Featuring Groq Technology for OpenAI
This could strengthen NVIDIA's position in advanced AI infrastructure, expand its custom silicon strategy beyond GPUs, and deepen ties with key AI developers, reinforcing its leadership in the rapidly evolving AI hardware ecosystem. The new system is expected to leverage architecture from Groq, the "acqui-hire" startup whose founder joined Nvidia last year. By moving toward Language Processing Units (LPUs), NVIDIA aims to solve the "bottleneck" of AI decoding. The platform would focus on inference computing and include a chip designed by startup Groq. This processor was designed to help and other customers build faster, more efficient AI systems. One source said Nvidia struck a US$20 billion licensing deal with Groq.
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Nvidia is set to launch a new processor incorporating Groq's design at its GTC conference next month, aimed at speeding up inference computing for AI systems. OpenAI will be the biggest customer, committing to 3GW of dedicated inference capacity following a $20-billion licensing deal between Nvidia and Groq that ended OpenAI's talks with competing chip startups.
Nvidia is preparing to unveil a new processor at its upcoming Nvidia GTC conference in San Jose next month, designed to help OpenAI and other customers build faster, more efficient AI systems, according to a Wall Street Journal report
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. The new platform focuses on inference computing, a form of processing that allows AI models to respond to user queries, and will incorporate a chip designed by startup Groq1
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Source: ET
The timing of this announcement matters significantly for the AI hardware ecosystem. OpenAI has been actively searching for solutions to accelerate AI processing, particularly for latency-sensitive AI workloads such as software development and AI-to-AI communication. The ChatGPT maker has expressed dissatisfaction with the speed at which existing hardware can deliver answers to users for specific types of problems
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.OpenAI has agreed to become one of the largest customers of the new Nvidia-Groq AI chip, representing a major win for Nvidia
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. The AI giant will allocate 3GW of dedicated inference capacity from the upcoming solution, which will be showcased at GTC 20262
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Source: Analytics Insight
This commitment follows OpenAI's recent announcement of $110 billion in fresh capital, driven by investments from Nvidia, SoftBank, and Amazon .
The partnership addresses a critical need for OpenAI, which requires new hardware to eventually provide about 10% of its inference computing needs in the future
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. Before settling on Nvidia's solution, OpenAI had discussed working with startups including Cerebras and Groq to provide chips for faster inference1
.Nvidia struck a $20-billion licensing deal with Groq that effectively shut down OpenAI's talks with competing chip providers
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. This licensing deal represents a strategic move by Nvidia to expand its custom silicon strategy beyond traditional GPUs and strengthen its position in advanced AI infrastructure3
.The new system is expected to leverage architecture from Groq, following an "acqui-hire" arrangement where Groq's founder joined Nvidia last year
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. By moving toward Language Processing Units (LPUs), Nvidia aims to solve the bottleneck of AI decoding that has plagued inference workloads3
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This development signals a shift in how major AI companies approach inference computing. While training large language models has dominated headlines, the ability to quickly generate responses remains crucial for user experience. OpenAI's decision to stick with Nvidia, despite exploring alternatives, suggests the upcoming solution built around Groq's LPUs is promising enough to warrant a 3GW capacity commitment
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.The partnership deepens ties between Nvidia and key AI developers, reinforcing Nvidia's leadership in the rapidly evolving AI hardware ecosystem
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. In September, Nvidia said it intended to pour as much as $100 billion into OpenAI as part of a deal that gave the chipmaker a stake in the startup and gave OpenAI the cash it needed to buy advanced chips . Industry watchers should monitor announcements from Nvidia at this year's GTC, which may also focus on Vera Rubin and possibly next-generation Feynman architectures2
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