Google in talks with Marvell to build new AI chips for TPUs, aiming to rival Nvidia GPUs
u/callsonreddit ·
Reddit — r/wallstreetbets
· April 19, 2026 at 16:14
· ⬆ 111 pts
· 💬 34 comments
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The post shares a news report indicating that Google is in discussions with Marvell Technology to develop two new custom AI chips, including a memory processing unit and a new TPU.
The strategic goal for Google is to make its TPUs a more efficient and viable alternative to Nvidia's GPUs for AI inference, boosting its cloud revenue.
Quality assessment: This is a news catalyst/report (citing The Information/Reuters) rather than original DD, but it contains highly actionable fundamental information regarding hyperscaler semiconductor supply chains.
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Source: https://money.usnews.com/investing/news/articles/2026-04-19/google-in-talks-with-marvell-to-build-new-ai-chips-for-inference-the-information-reports
Alphabet's Google is in talks with Marvell Technology to develop two new chips aimed at running AI models more efficiently, The Information reported on Sunday citing two people with knowledge of the discussions.
One of the chips is a memory processing unit designed to work with Google's tensor processing unit (TPU) and the other chip is a new TPU built specifically for running AI models, the report said.
Google has been pushing to make its TPUs a viable alternative to Nvidia's dominant GPUs. TPU sales have become a key driver of growth in Google's cloud revenue as it aims to show investors that its AI investments are generating returns.
Reuters could not immediately verify the report. Google and Marvell did not immediately respond to a request for a comment.
The companies aim to finalize the design of the memory processing unit as soon as next year before handing it off for test production, according to the report.
Google is in talks with Marvell to design two new AI chips, including a memory processing unit and a new TPU. Securing a custom silicon (ASIC) design win with a major hyperscaler like Google represents a massive future revenue stream and validates Marvell's custom compute capabilities. Go long on Marvell as it captures a larger share of the hyperscaler custom AI chip market. The report is currently unverified; talks could fall through or face design delays.
Google is aggressively developing custom silicon to make its TPUs a viable alternative to Nvidia GPUs. Vertically integrating AI hardware lowers inference costs, improves margins, and makes Google Cloud more attractive to enterprise AI customers. Long Google as it improves its AI infrastructure ROI and reduces reliance on expensive third-party GPUs. Custom silicon development is capital intensive and may still lag behind Nvidia's rapid innovation cycle.
Google is partnering with Marvell to build chips specifically aimed at rivaling Nvidia's dominant GPUs. As hyperscalers successfully develop and deploy their own custom silicon (TPUs, ASICs), it poses a long-term threat to Nvidia's pricing power and market share in AI inference. Monitor Nvidia's market share in hyperscaler inference as custom silicon alternatives mature. Nvidia's CUDA ecosystem moat remains incredibly strong, and custom chips often fail to match their general-purpose performance.
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