Perplexity targets a $30 billion valuation before a planned 2028 IPO, as Nvidia discusses a “not circular” funding-and-chip arrangement

Perplexity, the AI search and assistant startup, is reportedly trying to reach a $30 billion valuation ahead of a planned 2028 initial public offering, a milestone effort that could be supported by a high-profile investment relationship with Nvidia. The target valuation, as described in a market news report, frames Nvidia’s involvement as more than a passive bet on the AI boom and instead as part of a broader path to liquidity for a fast-scaling user-facing product.

The report also describes an unusual funding and procurement loop: Nvidia is said to be writing a check that helps fund Perplexity-linked operations, after which those operations would turn around and buy Nvidia chips. The specific mechanics of how capital flows are structured, what entity holds the chips, and whether the procurement is contractually tied to the investment were not laid out in the available account, leaving open questions about the exact commercial terms.

In the account, Nvidia CEO Jensen Huang is quoted as saying the arrangement is not “circular,” suggesting that the value proposition is grounded in performance and end demand rather than a purely accounting-driven exchange. Huang’s point, as presented, implies that the chips are purchased to satisfy real computational and product requirements, and the investment is aimed at enabling the business that generates that demand.

The catalyst for the valuation push is Perplexity’s revenue growth, described in the report as “explosive.” While the report characterizes the scale-up momentum, it does not provide the underlying numbers in the material available for this review, such as revenue range, growth rate, margins, or customer concentration. That gap matters because a $30 billion valuation would typically require investors to underwrite sustained demand, unit economics, and a clear path to profitability or durable margin expansion.

From Nvidia’s perspective, the narrative fits the long-running industry dynamic in which AI model developers and AI application companies require large volumes of accelerated compute, often using Nvidia’s data center platforms. When those applications scale, demand for GPUs and related infrastructure can follow, turning investment relationships and customer growth into practical chip consumption. That said, the existence of a funding-to-procurement linkage does raise the broader question investors often ask: how much of chip buying is driven by market need versus the economics of the investment structure itself.

Sector context also matters here. The AI market has seen repeated waves of fundraising, rapid product adoption, and a widening gap between companies that can secure compute at scale and those still fighting for access and cost efficiency. In that environment, IPO readiness can become as much a function of capital markets timing and corporate readiness as it is of operational performance, with pre-IPO valuations influenced by investor sentiment about AI demand durability.

A key caveat is what the report does not disclose. Beyond the high-level description, it does not provide contract documents, specific investment size, valuation assumptions, or the detailed structure governing whether chip procurement is guaranteed, discounted, or otherwise conditioned. It also does not specify which Nvidia products are involved, how long any procurement arrangement might last, or whether other chip suppliers are in the mix.

For now, the story’s near-term watch items are simple but important: whether Perplexity’s reported revenue trajectory is sustained, whether it can translate growth into improving economics, and how Nvidia frames similar investment-procurement relationships in future disclosures. If details emerge on the investment terms and the commercial logic of “not circular” economics, that could clarify how much these deals are strategic accelerants versus market optics ahead of an IPO.