# Model performance

dbt platform | Enterprise, Enterprise+

Catalog provides metadata on dbt runs for in-depth model performance and quality analysis. This feature assists in reducing infrastructure costs and saving time for data teams by highlighting where to fine-tune projects and deployments — such as model refactoring or job configuration adjustments.

To view model performance in Catalog:

1. Navigate to **Catalog** in the left-hand menu.
2. Select your project in the left sidebar.
3. Click the **Performance** tab.

[![Overview of Performance page navigation.](/img/docs/collaborate/dbt-explorer/explorer-model-performance.gif?v=2 "Overview of Performance page navigation.")](#)Overview of Performance page navigation.

On-demand learning

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## The Performance overview page

You can pinpoint areas for performance enhancement by using the Performance overview page. This page presents a comprehensive analysis across all project models and displays the longest-running models, those most frequently executed, and the ones with the highest failure rates during runs/tests. Data can be segmented by environment and job type which can offer insights into:

* Most executed models (total count).
* Models with the longest execution time (average duration).
* Models with the most failures, detailing run failures (percentage and count) and test failures (percentage and count).

Each data point links to individual models in Catalog.

[![Example of Performance overview page](/img/docs/collaborate/dbt-explorer/example-performance-overview-page.png?v=2 "Example of Performance overview page")](#)Example of Performance overview page

You can view historical metadata for up to the past three months. Select the time horizon using the filter, which defaults to a two-week lookback.

[![Example of dropdown](/img/docs/collaborate/dbt-explorer/ex-2-week-default.png?v=2 "Example of dropdown")](#)Example of dropdown

## The Model performance tab

The **Model performance** section in Catalog displays historical trends to help you identify optimization opportunities and understand model resource consumption.

[![Cost Insights in Catalog](/img/docs/dbt-platform/cost-insights/cost-insights-model.png?v=2 "Cost Insights in Catalog")](#)Cost Insights in Catalog

### Key metrics

The **Model performance** section displays the following metrics that summarize the overall cost and optimization impact for your project:

* **Total cost reduction**
* **Total % reduction**
* **Total query run time deduction**
* **Reused assets** (when dbt State or state-aware orchestration is enabled)

### Filters

Use the time period filter to customize the data you want to view: from the last 3 months up to the last 1 week.

For **Cost insights**, **Usage**, and **Query run time** tabs, you can set the view granularity by **Daily**, **Weekly**, or **Monthly**.

### Visualization tabs

* **Cost insights**: Shows the estimated warehouse costs incurred by this model and cost reduction from dbt State or state-aware orchestration.

* **Usage**: Shows the estimated warehouse usage consumed by this model over time. The **Usage** tab represents generic usage for your warehouse. The specific unit depends on your data warehouse:

  * Snowflake: Credits
  * BigQuery: Slot hours or bytes scanned (currently combined into one generic usage number)
  * Databricks: Databricks Units (DBUs)
  * Amazon Redshift Serverless: Redshift Processing Unit hours (RPU-hours)
  * Amazon Redshift Provisioned: Node-hours

* **Query run time**: Shows the estimated query execution time and the reduction in run duration from dbt State or state-aware orchestration.

* **Build time**: Shows average execution time for the model and how it trends over the selected period.

* **Build count**: Tracks how many times the model was built or reused, including any failures or errors.

* **Test results**: Displays test execution outcomes and pass/fail rates for tests on this model.

* **Consumption queries**: Shows queries running against this model, helping you understand downstream usage patterns.

### Table view

For **Cost insights**, **Usage**, and **Query run time** tabs, you can access the table view by clicking **Show table**, which provides detailed optimization data such as models reused, usage reduction, and cost reduction.

Use the **All** and **Jobs** buttons to switch between views:

* **All**: Shows aggregated cost data across all jobs in the project.
* **Jobs**: Shows cost data broken down by individual jobs.

When viewing the table, you can export the data as a CSV file using the **Download** button. When **Jobs** is selected, the CSV export includes job-level data.

### Chart interactions

For **Build time** and **Build count** tabs:

* Click on any data point in the charts to see a detailed table listing all job runs for that day.
* Each row in the table provides a direct link to the run details if you want to investigate further.

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