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Troubleshooting slow models

Speed of model loading/calculation in Causal depends on various factors:

- Model size (cell count mainly depends on number of time steps, number of category items, number of variables, number of scenarios)
- Complexity of the visuals (charts/tables)
- Complexity of the formulas (e.g. a sumif formula is slower than a simple addition)

If you’re having trouble with the speed / performance of your model, consider the following options:

- Turn on manual recompute. This will mean you can make multiple edits to the model, and then hit Recompute to evaulate them all at once. Hit the ⚙️ top right of the spreadsheet, and toggle
**Recompute manually**on under Calculation. - Hide the visuals pane (top-right of spreadsheet), and/or consider deleting unused visuals, or moving them to a separate model.
- If you’re using categories (including cohorts):
- Consider if you need the category on every variable in your model/s, or just some variables. You can aggregate away the category for the variables you don’t require the breakdown on.
- Consider if you can reduce the number of category items in the category (e.g. grouping all smaller category items into "other" instead of having them each as separate items).

- If you have one big model, consider splitting it up into smaller sub-models. Note that you can use our move variable functionality to make these changes easily.
- Consider removing scenarios that are no longer in use.
- If your model is connected to a data source, and the data source is large (either because of its granularity, its dimensionality/categories etc), then consider aggregating data in the data source instead of in Causal.
- Consider upgrading to a paying plan. Paying customers’ models run on dedicated infrastructure — the model will be cached in memory which makes recomputes faster + we only send the numbers you're looking at to the browser which makes large models more manageable.

Last modified 1mo ago

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