> ## Documentation Index
> Fetch the complete documentation index at: https://evalgate.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Pick a winner

> Turn the best variant into the new baseline.

# Pick a winner

Once a Playground run shows a candidate is better, you promote it. Winner
selection is an admin action and is recorded with the exact run, variant, and
decision.

## Step 1 — Open the winning run

On the Playground page, open the completed run that proves your candidate wins.

## Step 2 — Select the winner

Click **Select winner** on the candidate variant. Confirm. EvalGate records:

* the exact run snapshot,
* the selected variant ID,
* the request hash,
* the decision actor and rationale.

<Warning>
  Winner selection is **admin-only**. A non-admin can run the Playground but
  cannot promote a variant.
</Warning>

## Step 3 — Use the winner downstream

The winner feeds the next stages of the eval loop:

* An **Experiment** can be created from this Playground to confirm the win at
  scale.
* A **deployable artifact** can be derived from the winning prompt, model, and
  parameters.
* The **Unified Eval Loop** records this Playground as the "Playground
  reproduction" stage.

## What a winner is not

* It is not a deployment. You still publish and deploy the artifact separately.
* It is not irreversible, but the decision is immutable in history. To change
  direction, run a new Playground and pick a new winner.

## Up next

Carry the winner through [Deploy an artifact](../deployments/deploy-artifact).