Nvidia The next-generation Vera Rubin platform has obtained its first important independent benchmark test results, with a performance improvement that is significant enough to present another issue for AI company: the cost of keeping up with Nvidia hardware iterations is becoming increasingly high.
Nvidia disclosed this result in its official MLPerf announcement, describing Vera Rubin's participation as a preview submission before wider deployment.
This point is very important: a 3.7-fold improvement is the best result measured on a specific workload, and it does not mean that all AI applications will suddenly become 3.7 times faster.
Nvidia made last year's AI infrastructure seem outdated very quickly
This benchmark test also demonstrates how rapidly the underlying economic structure is changing.
Nvidia indicates that four GB300 NVL72 racks, totaling 288 GPU, have achieved 99% expansion efficiency, and software improvements alone have led to a performance boost of up to 1.6 times, which is higher than the results of the previous round of MLPerf.
This means that the replacement cycle is exceptionally fast. AI Cloud operators are not simply increasing GPU, but are repeatedly weighing whether the existing clusters can still compete with the updated system, as the new system can produce more token per rack, per megawatt.
Performance competitions are turning into financing competitions.
And thus, the story no longer remains confined to Nvidia.
CoreWeave recently increased the issuance scale of its convertible bonds from $3 billion to $3.7 billion, adding another round of major financing to an industry that has already consumed a large amount of debt and equity funds. Reports suggest that this demonstrates how GPU's expansion is rapidly translating into pressure on its balance sheet.
The same issue extends to the entire industry. Nebius has also turned to billions of dollars in financing, while the broader AI infrastructure boom is increasingly being funded by debt.
Nvidia believes that higher throughput can reduce the cost per token, which means that new hardware may ultimately justify its investment through better economic efficiency. However, Nvidia has not yet made available a simple rack price for investors to directly compare the 3.7-fold benchmark test improvement with the procurement costs.
Maya Bennett
Maya Bennett is a financial journalist with experience reporting on cryptocurrencies, stocks, and broader market trends. Her areas of focus include Bitcoin, major digital assets, the stock market, monetary policy, as well as economic developments that influence investor sentiment. She is adept at transforming rapidly changing market news into clear and concise reports.
