# Virtual Models

Vercel introduced Virtual Models on AI Gateway, so apps and agents call a task-named virtual model ID instead of a concrete model name, with model choice, fallbacks and Zero Data Retention configured on the gateway. Previously switching models was a one-line code change that still usually required a redeploy; now editing the virtual model is picked up by every app and agent using that ID within a few minutes.

Vercel introduced Virtual Models on AI Gateway, so apps and agents call a task-named virtual model ID instead of a concrete model name, with model choice, fallbacks and Zero Data Retention configured on the gateway. Previously switching models was a one-line code change that still usually required a redeploy; now editing the virtual model is picked up by every app and agent using that ID within a few minutes.

AI Gateway now offers virtual models: a saved configuration naming which model to use and with which settings, called by apps and agents through a custom model ID such as vmc/coding-agent. Previously, changing the model or settings meant redeploying apps or reconfiguring agents; now the change happens centrally in AI Gateway. It can also supply options a coding agent does not expose, such as reasoning effort, fast mode and prompt caching, and carry provider choice, fallback models and Zero Data Retention requirements.

AI Gateway now offers virtual models: a saved configuration naming which model to use and with which settings, called by apps and agents through a custom model ID such as vmc/coding-agent. Previously, changing the model or settings meant redeploying apps or reconfiguring agents; now the change happens centrally in AI Gateway. It can also supply options a coding agent does not expose, such as reasoning effort, fast mode and prompt caching, and carry provider choice, fallback models and Zero Data Retention requirements.