OpenAI's Jalapeño chip packs 1.5–1.9x more inference into every watt
OpenAI's first custom inference chip, Jalapeño, is now posting first results, and they're strong: 1.5–1.9x more AI work per watt at peak throughput and 1.7–3.6x lower end-to-end latency than leading commercial systems, with 2.1–4.1x gains on highly interactive agent workloads. The architecture delivers both throughput and latency at once, where rivals typically trade one for the other. It holds up across OpenAI- and third-party models alike, and marks a move toward owning the whole silicon-to-software stack.