Custom chip tops Nvidia in tests
OpenAI's custom inference chip, code-named Jalapeño, beat Nvidia's GB300 in third-party benchmark tests, according to results published this week. The chip led on tokens per user and throughput per kilowatt, a key measure of energy efficiency. The tests were run by independent reviewers, not by OpenAI itself.
Built with Broadcom
The Jalapeño chip was built with Broadcom, the result of a multi-year partnership. OpenAI started designing its own silicon to reduce its reliance on Nvidia, which dominates the AI chip market. The company still buys Nvidia processors in large volumes, but custom chips give it more control over cost and performance.
What the results mean
Analysts said the benchmark results are a milestone for OpenAI's hardware push. If the chip scales well, it could change the economics of AI computing. Lower energy use per token means lower operating costs for large language models. OpenAI runs some of the biggest AI workloads in the world, so even small efficiency gains translate into large savings.
The company has been expanding its hardware team and recently opened a chip design office. Industry observers say OpenAI could deploy Jalapeño chips in its data centers within the next year. Nvidia remains the market leader by a wide margin, but the test results show that challengers are closing the gap. Other companies, including Google and Amazon, have also built custom AI chips. The race to design better and cheaper AI hardware is now one of the most watched contests in technology. For OpenAI, the chip is part of a broader strategy to control its own computing future, from models to the silicon they run on.
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