As Nvidia prepares to report soaring revenues driven by data centre sales and new chip platforms, investors are increasingly cautious about the company’s financing strategies and the timing of its next-generation processors amidst rising competition in AI hardware.
Nvidia is heading into its latest results with investors looking beyond another quarter of rapid growth and towards a more difficult question: whether the company can keep turning the AI build-out into durable demand. Reuters reported that analysts expect second-quarter revenue to almost double from a year earlier to $92.18 billion, driven largely by data centre sales, but the focus has shifted to how quickly customers move from Blackwell to the next-generation Vera Rubin processors, which are due to start shipping this autumn.
That transition matters because Nvidia remains the dominant supplier to the AI infrastructure boom, yet its shares have lagged some peers this year as concerns grow about the way the company is recycling capital back into the sector. Reuters noted that Nvidia has helped arrange $500 billion in financing for customers building AI infrastructure and has separately agreed to guarantee up to $105 billion for OpenAI’s planned data-centre lease in Ohio, moves that have sharpened debate over whether the industry is relying on increasingly circular funding structures.
Chief executive Jensen Huang has defended the approach, arguing that Nvidia is using its cash-rich balance sheet to support customers that are expanding quickly but are not yet profitable. In his account, the Ohio commitment is not circular financing because OpenAI will pay for the lease, while Nvidia is helping secure the buildings, power and facilities needed to house its chips for years to come. That explanation has not fully quietened sceptics, however, including investors who worry that AI spending may be inflated by back-to-back financing arrangements rather than pure end-demand.
The stakes are high because competition is intensifying. Big Tech is also developing its own chips, while Intel and AMD are pushing harder into inference workloads, where AI systems answer queries and automate tasks. Morgan Stanley has estimated that Nvidia’s Rubin family could contribute nearly $9 billion in sales in the quarter ending in October, and analysts expect the company to signal that Rubin will improve the economics of AI factories even further than Blackwell. Separate reporting on Nvidia’s new Rubin platform suggests it will combine multiple chips, including specialised accelerators, to improve efficiency across different AI tasks, while recent industry accounts have also pointed to large Rubin-based infrastructure projects and a more fragmented inference architecture designed to split workloads between compute-heavy and bandwidth-optimised chips.
For now, Wall Street is still assuming Nvidia can deliver another step-up in sales. Analysts expect third-quarter revenue of $104.20 billion, up 82.8% year on year, with gross margins holding near 75% in the second and third quarters. But the market’s longer-term verdict is likely to depend less on one strong earnings report than on whether Rubin arrives on schedule, whether customers continue to spend at the current pace, and whether Nvidia can prove that its central role in AI infrastructure is creating real growth rather than merely financing it.
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