curl, your own backend, or any OpenAI-compatible client.
benchgen-router-lite, a model you uploaded, or one you fine-tuned in Train. If you don’t have a deployed model yet, see Deploy an Inference Model.Step 1: Open your model
In Models, find the model you want a key for, it needs to be Deployed or Running to serve an endpoint. Here,benchgen-router-lite is running.

AI Models: a running router (benchgen-router-lite) and deployed models beneath it

The Model Card tab, with the same Generate key shortcut already sitting in the sidebar
Step 2: The quick way, or the full API Keys tab
Click that sidebar Generate key button any time you just need a key fast. For naming keys or seeing everything you’ve already issued, click the API Keys tab instead, it’s the same action dialog either way, just with more around it.
The API Keys tab: endpoint, key name field, Generate key, and a table of existing keys
Step 3: Copy the key now, it won’t be shown again
A dialog shows your new secret key plus a ready-to-run example request.
The new API key dialog: the secret key, a Copy button, and an example curl request using it
Managing keys afterward
Your new key appears in the table on the API Keys tab, Active, with its creation date, last-used timestamp, and running spend. Click Revoke on any key you no longer want live, it flips to a Revoked status immediately and stops authenticating.
A revoked key: status changes to Revoked and its Revoke button disappears
Watching it get used
Every call made with the key rolls up into the model’s Usage tab: total requests, tokens, spend, and average latency, plus a log of every individual request.
The Usage tab after two calls: requests, tokens, spend, and latency, with each call logged below

One request opened: tags, request details, metrics, and cost so far, with the full prompt and response below