> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Compare runs with Eval Tables
Use Eval Tables to compare inputs, outputs, and scores across multiple runs. W\&B aligns corresponding examples and calculates aggregate scores and score differences for the selected runs.
To compare runs with workspace-level summary metrics, line plots, pinned runs, or a baseline run, see [Pin and compare runs](/models/runs/compare-runs). Eval Tables compare aligned examples and Eval Table-specific scores within a logged table.
To compare runs:
1. Navigate to your project workspace.
2. Scroll to the Eval Tables panel.
3. Select the **+** button.
4. Select the run that you want to add.
W\&B groups columns that have the same role and name across the selected runs. For example, if two runs use the same `input_columns`, W\&B displays those columns together in the **Inputs** section. W\&B similarly groups shared `output_columns` and `score_columns` in the **Outputs** and **Scores** sections.
The following screenshot shows an Eval Table that compares the `summer-butterfly-9` and `gentle-flower-8` runs:
## Set the reference run
When you compare multiple runs, W\&B defaults to designating the left-most run as the reference run. The reference run is the baseline to calculate score deltas.
To choose a different reference run, hover over the run, open its menu, and select **Set as reference**.
## View aggregate scores
W\&B calculates an aggregate value for each score column in each selected run. The calculation depends on the score's data type:
| Type of score | Aggregate value |
| --------------------- | ----------------------------------- |
| Boolean | Count and fraction of `true` values |
| Numeric | Mean |
| String or categorical | No scalar aggregate |
| Null | Excluded from calculation |
The following screenshot highlights the aggregate values for the correct and confidence scores:
## Compare score deltas
For each score column, W\&B calculates the difference between the reference run and every other selected run.
W\&B calculates each delta as:
```text theme={null}
comparison run value - reference run value
```
For example, suppose `summer-butterfly-9` is the reference run and `gentle-flower-8` is the comparison run. W\&B calculates the confidence delta as follows:
| `summer-butterfly-9` | `gentle-flower-8` | delta |
| -------------------- | ----------------- | ----- |
| 0.43 | 0.62 | +0.19 |
| 0.92 | 0.86 | -0.06 |
| 0.97 | 0.85 | -0.12 |
A positive delta means that the comparison run has a higher value than the reference run. A negative delta means that it has a lower value.
The following screenshot highlights the score deltas:
