What matters when choosing a relay
An AI API relay is only useful if it behaves like a clean transport layer instead of another point of friction. The first thing to check is whether the endpoint is truly OpenAI-compatible in the parts your application already depends on: request shape, authentication style, streaming behavior, and error format. Compatibility reduces migration work, but it also matters for day-two operations, because your logs and retry logic should still make sense when a request fails.
Price is the next obvious criterion, but it should be read as operating cost, not just headline rate. A pay-as-you-go model can be a better fit than prepaid bundles when traffic is irregular, because it keeps experimentation and low-volume production usage aligned with real consumption. That is why search terms like GPT API便宜 and 按量付费 show up together in practical comparisons: users are usually trying to balance cost with control, not chase the lowest number in isolation.
Reliability is where a relay proves itself. You want predictable latency, sane rate-limit behavior, and clear failures that can be retried or surfaced upstream. A relay such as https://59api.com is worth evaluating only after it passes a few simple smoke tests in your own stack.