I’m seeing different throttling behavior from two projects that belong to the same OpenAI organization. Before I redesign our request queue, I’m trying to understand what actually determines the effective limit: the project, the organization, the model, or some combination.

Has anyone tracked down why project-level rate limits can feel inconsistent across otherwise similar workloads? I’m especially interested in what usage details are worth comparing when a request starts returning rate-limit errors.