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

# Router Evals

> Add benchmark scores as evidence for model selection.

Router evals are model scorecards. Create one from **Evals** in the dashboard, then upload a CSV:

```csv theme={null}
model_id,score,thinking_level,notes
openai/gpt-5.6-sol,87,high,Strong public run
openai/gpt-5.6-sol,82,off,Non-reasoning run
anthropic/claude-sonnet-4-6,81,,Generic score
```

`model_id` and `score` are required. Higher scores are better. `thinking_level` and `notes` are optional. Model IDs must exactly match the provider-prefixed IDs enabled on the router, and each model/level pair must be unique.

Import the eval from the router create or edit page. Dari prefers a score matching both model and reasoning level, then falls back to that model's row with a blank level. Scores inform selection; they do not define a fixed formula.