One Endpoint, Four Coding Models: A Practical Switching Workflow

Disclosure: I work on Vancine, the API platform used in the examples below. This article was prepared with AI assistance and reviewed against the live product documentation. Coding agents do not always need the same model. One task may benefit from an experimental vision-capable model. Another may need a lightweight flash model for a fast edit-test loop. The integration problem is that evaluating several models often means managing different endpoints, credentials, and request formats. An OpenAI-compatible endpoint makes the comparison simpler: keep the client configuration fixed and change only the model field. The four model IDs This workflow uses four exact model IDs: hy4-preview deepseek-v4-flash-vision-exp glm-5.3-flash qwen3.8-flash They are available through the same base URL: https://vancine.com/v1 Current prices and catalog metadata can change, so I am deliberately not freezing them into this article. The live comparison page reads them from the pri