Virtual models now available on AI Gateway
AI Gateway Virtual Models now let apps and coding agents use a task ID for centrally managed model settings, routing, and spend tags. They can also set options an agent may not expose directly.
AI Gateway Virtual Models are saved configurations addressed by IDs such as **vmc/coding-agent**. Teams can centrally set the model, reasoning effort, fast mode, prompt caching, provider routing, fallbacks, Zero Data Retention, and reporting tags.
Builders can point compatible API requests or coding agents at a virtual model to manage these settings without reconfiguring each caller. This is useful when agent harnesses expose only a subset of provider options.
AI Gateway Virtual Models are saved configurations addressed by IDs such as **vmc/coding-agent**. Teams can centrally set the model, reasoning effort, fast mode, prompt caching, provider routing, fallbacks, Zero Data Retention, and reporting tags. Builders can point compatible API requests or coding agents at a virtual model to manage these settings without reconfiguring each caller. This is useful when agent harnesses expose only a subset of provider options. The changelog says virtual models work with every model type on AI Gateway, but does not detail which settings each agent harness supports or how configuration changes are tested.
This changelog confirms the stable-ID approach as a saved, centrally managed configuration spanning more routing and compliance controls than the blog’s shorter overview lists. It strengthens the practical case for configuring agent behavior outside individual callers, while leaving harness support and configuration testing unspecified.