How OpenAI Used Its Own LLMs to Design Its Jalapeño Chip
OpenAI's Jalapeño AI accelerator, co-designed with Broadcom, went from concept to silicon in under 20 months using LLM-driven design workflows.
OpenAI unveiled Jalapeño, its debut AI accelerator delivering up to 13.4 petaflops of 4-bit compute with 232GB of memory accessed at 15.4 TB/s, and citing up to 3.6x lower end-to-end latency than Nvidia's GB300. The chip moved from first architecture concept to first silicon in under 20 months, with only nine months between first RTL and tape-out, aided by internal LLMs and Google's open-source XLS high-level synthesis toolchain. A team averaging fewer than 100 people handled system design while Broadcom managed physical design from the gates onward. OpenAI's internal models also lifted a DeepSeek multi-head latent attention kernel from 0.31% to 88.94% of theoretical peak in roughly 40 hours.