Jalapeño: benchmark claims need a workload check

OpenAI reports that its Jalapeño inference system outperformed comparison systems on the public InferenceX benchmark across throughput per watt and end-to-end latency for three open-weight models. Why it matters: Inference hardware can affect response latency and serving economics, especially for multi-step agents. But a vendor benchmark is not evidence that a buyer's model mix, traffic shape, availability, or cost will improve.

Try this: For the next hosting or capacity decision, record tokens per second per watt, time between tokens, end-to-end latency, and cost per completed task on one representative workload; compare those results before treating provider chip claims as routing input.