> For the complete documentation index, see [llms.txt](https://docs.rootcause.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rootcause.ai/more-details/digital-twin/model-comparison.md).

# Model Comparison

Causal models evolve. You might train a Digital Twin on January data, then retrain on February data. Or experiment with different configurations — omitting certain variables, adding domain knowledge, changing temporal settings.

Model Comparison lets you put two Digital Twin versions side by side and understand exactly what changed: which relationships appeared, disappeared, or reversed direction, and how the underlying probability distributions shifted.

This is essential for model governance. Before promoting a new model version, you need evidence of how it differs from the current one.

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### Accessing Model Comparison

Model Comparison is its own page, not a tab on the twin: the **Compare** page under the Digital Twins section of your workspace (at `…/twins/compare`). The twin and version selectors are in the upper right corner.

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### Selecting models

The comparison tool lets you compare any two Digital Twin versions — including versions from different twins.

Common scenarios:

* **Same twin, different versions** — track how the model evolved over retraining
* **Same data, different configurations** — compare the effect of constraints or excluded variables
* **Different time periods** — see how causal relationships changed between datasets

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### Comparing twins

Once two models are selected, the comparison view shows both causal graphs side by side with structural differences highlighted.

<figure><img src="/files/TgjLwC1wxoX57RGyhvK8" alt="The Compare page in Separate view: the v1.1.0 and v1.0.0 graphs with a Comparison Overview panel reporting 19 variables and 31 relationships in each, 31 common edges, and a 71.3% evaluation for both"><figcaption><p>Two versions compared in the Separate view. The Comparison Overview reports size, structural overlap, and evaluation for both models.</p></figcaption></figure>

Switching to **Diff** merges both graphs into a single view, color-coding the edges unique to either model and any whose direction changed. The **Comparison Overview** panel summarizes the structural overlap, evaluation, equations, and parameters, with **Details** links into a full breakdown of each.

<figure><img src="/files/YFOLGQpkxPVCfTUbzbMB" alt="The Compare page in Diff view: a merged graph with a legend for Model 1 Only, Model 2 Only, Both Models, and Direction Changed"><figcaption><p>The merged diff view. With 31 common edges and no unique ones, these two versions share an identical structure.</p></figcaption></figure>

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### Interpreting differences

**Structural changes**

* **New edges** — the model found a relationship not present before; may reflect new patterns in updated data
* **Removed edges** — a previously discovered relationship is no longer supported; may indicate data drift
* **Direction changes** — causality now flows the opposite way; investigate why

**Parameter changes**

Even when structure is identical, parameters can differ. The conditional influence between variables may have become stronger, weaker, or changed in functional form.

**Questions to ask**

1. Are structural changes expected given the data differences?
2. Do direction changes make domain sense?
3. Would these changes affect downstream decisions?

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### Creating a second twin to compare

To compare two configurations or time periods, create a second Digital Twin from the same (or a different) Data View. Both twins will then be available in the Compare page selectors.

For Digital Twin creation steps, see [Build Digital Twin](/user-guide/creating-digital-twin.md).