Qingzhong API is a paid AI API service built for developers who need a place to review model prices, configure API credentials, and inspect their application's requests. We are submitting this introduction as the project team. The service website is https://web.qzwlapi.top. The API base URL is https://api.qzwlapi.top/v1. Keeping these addresses separate helps distinguish the account dashboard from the endpoint used by an application.
Before connecting a client, developers can open the public model and pricing page at https://web.qzwlapi.top/pricing. Availability, model identifiers, billing information, and any usage restrictions should be checked there rather than copied from an old promotional screenshot. We do not publish a fixed price table in this introduction because the live pricing page is the appropriate reference when deciding whether to use the service.
The account dashboard provides API key management, usage records, and support tickets. A practical setup starts by creating a key for a particular application, entering the API base URL in that client's custom provider settings, and selecting a model identifier from the current model page. A short first request is useful for checking the connection and its usage record before sending a larger workload. Developers should keep their credentials private and avoid committing keys to repositories or including them in public screenshots.
The setup guide at https://web.qzwlapi.top/docs explains the web and API entry points. One common configuration mistake is repeating the version prefix: a client that automatically adds /v1 needs the service host configured according to that client's instructions, whereas a client that expects the complete base URL can use https://api.qzwlapi.top/v1. The precise setting depends on the client, so the guide and client documentation should be checked together.
When troubleshooting, authentication errors, an incorrect route, model availability, rate limits, and an interrupted streaming response need different checks. Recording the approximate request time and the error message gives support a starting point. A support ticket is available from the dashboard, and the developer should redact credentials before attaching logs. Usage records help connect an application's requests with its account activity rather than leaving the developer to infer the result from a client screen alone.
There is also a publicly verifiable sample report at https://apiranking.com/verify/report/KT1LpGC5oEA. That report concerns the tested gpt-6-astra endpoint and reports a 100 percent model matching result for that sample. It is not a claim that every model, capability, network connection, or request has a perfect score. Readers can inspect the report themselves and assess what its checks establish.
API usage is paid according to the applicable model and account settings. We recommend reviewing pricing and permitted uses before integrating the service into an application. Feedback about unclear setup instructions, confusing price presentation, or missing details in usage records is welcome through the project's support channel.
