
OpenAI has unveiled Jalapeño, a custom inference chip developed with Broadcom, which early testing shows delivers better performance-per-watt than existing options. By building its own chip alongside models and data centers, OpenAI aims to lower the cost of serving AI responses to users and reduce its dependence on Nvidia.
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OpenAI announced Jalapeño, a custom-built inference processor designed with Broadcom. The chip is still being tested, but early results show significantly better performance-per-watt than current alternatives, according to the company.
Why it matters
Running AI models to answer user requests (inference) is a major cost for OpenAI. A more efficient chip for this task could substantially lower operating expenses. Google and Amazon have already built similar custom chips for the same reason.
What to watch
Jalapeño is optimized specifically for inference workloads like real-time coding models. More demanding tasks such as pre-training are still expected to rely on Nvidia hardware. The company is integrating the chip as part of a broader strategy to control its entire stack—from model development to data center operations to hardware.
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