What Nvidia’s $20B Groq Deal Says About the Next AI Hardware Opportunities in Late-Stage Venture

Nvidia’s recent $20 billion acqui-hire of Groq is more than a single high-profile transaction — it’s a clear signal that consolidation in AI hardware is accelerating. As competition for AI compute intensifies, large incumbents are moving quickly to secure differentiated architectures, talent, and intellectual property. Groq’s exit follows a broader pattern: Intel has reportedly explored acquiring SambaNova, while Meta has been tied to Rivos. Other AI chip startups have either been absorbed, shut down, or forced to narrow their focus. The result is a rapidly shrinking field of independent AI hardware companies capable of operating at scale.

This consolidation is reshaping the private-market AI hardware ecosystem. Over the past decade, dozens of startups set out to challenge GPUs with novel designs optimized for AI workloads. Today, only a handful remain credible stand-alone platforms. Some, like Tenstorrent, are pursuing an IP-licensing and RISC-V–based strategy. Others, such as d-Matrix, are focused narrowly on memory-centric inference acceleration. Meanwhile, hyperscalers continue to design custom silicon in-house, limiting the addressable market for third-party vendors. In this environment, independence itself is becoming scarce.

Against this backdrop, Cerebras Systems represents a significant case study in independent scaling within the AI hardware sector. Its Wafer-Scale Engine (WSE) remains one of the most distinct architectural bets in the industry. By utilizing a single silicon wafer rather than a cluster of smaller GPUs, Cerebras aims to bypass the interconnect bottlenecks that often slow down massive model training.

However, maintaining independence in a market dominated by Nvidia’s R&D cycle presents immense operational challenges. The capital-intensive nature of wafer-scale manufacturing means Cerebras must sustain high-yield rates on a much larger surface area than traditional chipmakers. That has been a technical hurdle that remains a point of intense scrutiny for industry observers. Furthermore, while Cerebras has built a bespoke software stack to support its hardware, it must continue to compete against the deep-rooted "CUDA moat" that has standardized much of the developer ecosystem.

While recent reports indicate substantial revenue growth from Cerebras, climbing from ~$25 million in 2022 to over $200 million in 2024, questions remain regarding the company's path to long-term profitability and its ability to diversify a historically concentrated customer base. As Cerebras reportedly prepares for a 2026 public listing, its performance will serve as a critical barometer for whether an independent, hardware-first platform can survive the accelerating consolidation that recently claimed Groq. In this environment, the company's future depends as much on its ability to manage massive capital expenditures as it does on its innovative silicon.

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THEMATIC RESEARCH DISCLOSURE: This article is for informational purposes only and represents the thematic analysis of Prepublic Equity Partners ("PEP"). This content is intended to discuss industry trends and does not constitute investment advice, a recommendation, or a solicitation to buy or sell any securities. PEP is not a registered investment adviser or broker-dealer.

Private company data and "pre-IPO" mentions are based on available market reports and have not been independently verified. Investing in late-stage venture capital involves high risk and illiquidity. PEP or its affiliates may hold financial interests in the companies or sectors discussed, and we reserve the right to trade these positions at any time without notice.