# Vercel — Introducing Virtual Models on AI Gateway

- Company: Vercel (vercel.com)
- Announced: 2026-10-28T07:25:00+00:00
- Category: capability-change
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://vercel.com/blog/ai-gateway-virtual-models
- Record: https://forck.live/items/29058-introducing-virtual-models-on-ai-gateway
- Subject: v0 / AI SDK / AI Gateway

Vercel is adding Virtual Models to AI Gateway, letting teams point apps and agents at a single model ID that can be reconfigured without code changes or redeploys. The feature abstracts the model string and its settings, so a task like coding-agent can be created with a CLI command and then called as vmc/coding-agent wherever that task runs. Vercel says 125 new models from more than 10 labs arrived on AI Gateway in the last 90 days, about 10 a week, and that switching between them previously meant editing a line of code and redeploying. Editing a virtual model, for example from anthropic/claude-opus-5.5 to openai/gpt-6.1-sol, propagates to every app and agent calling that ID within a few minutes. Settings such as fallbacks, Zero Data Retention and tags stay with the virtual model when the underlying model changes, and they override the same settings in a request, so callers cannot change provider order or failover. Vercel advises pointing a second virtual model at a new model and running evals against it before switching one that serves production traffic. Virtual Models work with every model type on AI Gateway, including image, video, speech, embedding and realtime models, and with the AI SDK and the OpenAI- and Anthropic-compatible APIs.

## Evidence

Verbatim from https://vercel.com/blog/ai-gateway-virtual-models:

> Today, we are introducing Virtual Models on AI Gateway .
> 
> Virtual Models are an abstraction of the model string and configurations your apps and developers use. With a single virtual model ID, you can change and update models, configure fallbacks and priority, and enforce Zero Data Retention centrally. The virtual model configuration applies wherever the ID is used.
> 
> Assign a virtual model ID to an agent task, and pass it as the model string wherever that task is called. You can then change the model and settings behind the virtual model ID in AI Gateway, and your apps and agents will pick up the new configuration automatically, without code changes or redeploys.
> 
> Copy link to heading New models use the same virtual model ID
> 
> In the last 90 days, 125 new models from more than 10 labs became available on AI Gateway. That adds up to about 10 a week. AI Gateway already makes switching a one-line change. You call any of those models by ID, and AI Gateway routes each request to a healthy provider and can fall back to others when one fails.
> 
> That one line still lives in your code, so switching usually means a redeploy.

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