In the AI application development process, model selection is an iterative process, and developers need to frequently test the performance and suitability of different models. While traditional development methods require modifying a large number of API calls and related code every time a model is switched, Vercel AI Gateway makes model switching easier than ever with a unified interface design and standardized model identifiers.
Development practice has shown that switching models through AI Gateway requires only one parameter to be modified: each model has a standard identification of 'vendor/model name' (e.g., 'anthropic/claude-sonnet-4 ' or 'xai/grok-4'), and keeping all other code unchanged allows calling different models. For example, a developer can first test the quality of text generation with OpenAI's GPT-4, and then simply change the model parameter to 'anthropic/claude-3' to test the performance of the same cue under that model, without rewriting any authentication or network request logic. This design significantly shortens the model selection cycle and allows developers to focus on comparing results rather than integration issues.
This answer comes from the articleVercel AI Gateway: a gateway to manage and optimize AI application requestsThe
English 
简体中文 
日本語 
Deutsch 
Português do Brasil