Virtual models are now available on AI Gateway.
A virtual model is a saved configuration that tells AI Gateway which model and settings to use. Your apps and agents call it with a custom model ID, such as vmc/coding-agent. You can change the model or settings centrally in AI Gateway without redeploying your apps or reconfiguring your agents.
Use virtual models to:
Configure coding agents: Set reasoning effort, fast mode, prompt caching, and other options even when your agent doesn’t expose them.
Control routing and compliance: Choose providers, configure fallback models, and enforce requirements such as Zero Data Retention.
Attribute spend: Attach custom reporting tags to every request that uses the virtual model.
To create a virtual model, open the Virtual Models page and click Create Virtual Model. Enter a slug, choose the underlying model, configure the settings you want requests to use, and save.
Or create one with the Vercel CLI:
vercel ai-gateway virtual-models create coding-agent \ --model anthropic/claude-opus-5.5 \ --config '{"speed":"fast","zeroDataRetention":true}'Create a reusable coding-agent configuration with fast mode and Zero Data Retention.
To use a virtual model, replace the provider model ID in your AI SDK or compatible API requests with vmc/<slug>, such as vmc/coding-agent.
For coding agents, connect to AI Gateway with vercel ai-gateway setup if needed, then select your virtual model in the agent’s model picker or configuration.
Virtual models work with every model type on AI Gateway. Read the launch post for examples or learn more in the virtual models documentation.