> ## Documentation Index
> Fetch the complete documentation index at: https://wb-21fd5541-style-guide-models-runs-20260604-113608.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Delete runs

> Delete runs from a W&B project using the W&B App or the Python SDK, and learn how deleted run data is removed from storage.

This page shows how to delete runs from a W\&B project interactively in the W\&B App or programmatically with the W\&B Python SDK. This page also explains the logic W\&B uses to remove deleted run data from object storage on self-managed deployments.

Based on your use case, select one of the following tabs to learn how to delete a run:

<Tabs>
  <Tab title="W&B App" value="ui">
    1. Navigate to the project that contains the runs you want to delete.
    2. Select the **Runs** tab.
    3. Select the checkbox next to the runs you want to delete.
    4. Select the **Delete** button (trash can icon) above the table.
    5. From the drawer that appears, select **Delete**.

    For projects that contain many runs, use the search bar to filter runs with Regex, or use the filter button to filter runs by status, tags, or other properties.
  </Tab>

  <Tab title="Python" value="python">
    You can delete runs programmatically with [`wandb.apis.public.Run.delete()`](/models/ref/python/public-api/run#method-run-delete). To also remove artifacts associated with the run, set `delete_artifacts=True`.

    Replace `[ENTITY]` with your W\&B entity name and `[PROJECT]` with your project name.

    ```python theme={null}
    import wandb

    api = wandb.Api()
    runs = api.runs("[ENTITY]/[PROJECT]")
    for run in runs:
        if run.state == "finished":  # Replace with your own condition
            run.delete(delete_artifacts=False)
    ```

    To remove individual files attached to a run, like logged media:

    1. Obtain the relevant file handles with [`Run.files()`](/models/ref/python/public-api/run#method-run-files).
    2. Use [`File.delete()`](/models/ref/python/public-api/file#method-file-delete) to delete individual files.
  </Tab>
</Tabs>

You can't reuse a run ID, even after you delete the run. If you try to start a new run with that ID, it fails with an error.

<Warning>
  When you delete a run and choose to delete associated artifacts, the artifacts are permanently removed and can't be recovered, even if the run is restored later. This includes artifacts linked to the Registry.
</Warning>

## Run deletion flowchart

The following diagram illustrates the run deletion process, including how W\&B handles associated artifacts and Registry links:

```mermaid theme={null}
graph TB
    Start([User Initiates<br/>Run Deletion]) --> RunSelect[Select Runs<br/>to Delete]
    RunSelect --> DeletePrompt{Delete Associated<br/>Artifacts?}
    DeletePrompt -->|No| DeleteRunOnly[Delete Run Only<br/><br/>- Run metadata removed<br/>- Artifacts remain available<br/>- Can still access artifacts]
    DeletePrompt -->|Yes| CheckArtifacts[Check for<br/>Associated Artifacts]
    CheckArtifacts --> HasRegistry{Artifacts Linked to<br/>Model Registry?}
    HasRegistry -->|Yes| RegistryWarning[Warning<br/><br/>Registry models will be deleted<br/>Production aliases affected]
    HasRegistry -->|No| DirectDelete
    RegistryWarning --> ConfirmRegistry{Confirm Registry<br/>Model Deletion?}
    ConfirmRegistry -->|No| DeleteRunOnly
    ConfirmRegistry -->|Yes| DirectDelete[Delete Run + Artifacts<br/><br/>- Run metadata removed<br/>- Artifacts permanently deleted<br/>- Registry links removed<br/>- Cannot be recovered]
    DeleteRunOnly --> PartialEnd([Run Deleted<br/>Artifacts Preserved])
    DirectDelete --> FullEnd([Run + Artifacts<br/>Permanently Deleted])
    style Start fill:#e1f5fe,stroke:#333,stroke-width:2px,color:#000
    style DeletePrompt fill:#fff3e0,stroke:#333,stroke-width:2px,color:#000
    style RegistryWarning fill:#ffecb3,stroke:#333,stroke-width:2px,color:#000
    style DirectDelete fill:#ffebee,stroke:#333,stroke-width:2px,color:#000
    style DeleteRunOnly fill:#e8f5e9,stroke:#333,stroke-width:2px,color:#000
    style PartialEnd fill:#c8e6c9,stroke:#333,stroke-width:2px,color:#000
    style FullEnd fill:#ffcdd2,stroke:#333,stroke-width:2px,color:#000
```

## When deleted run data is removed from storage

On [W\&B Dedicated Cloud](/platform/hosting/hosting-options/dedicated-cloud) and [W\&B Self-Managed](/platform/hosting/hosting-options/self-managed), the `GORILLA_DATA_RETENTION_PERIOD` environment variable controls how long W\&B retains deleted run data before permanently removing it from object storage. This setting doesn't remove artifacts. Artifacts follow the deletion and garbage collection flow described in [Delete an artifact](/models/artifacts/delete-artifacts).

When you set or change `GORILLA_DATA_RETENTION_PERIOD`, the effect is irreversible for data past the retention window. Back up your database and bucket before you enable or tighten retention. For the reference table and warnings, see [Configure environment variables](/platform/hosting/env-vars).

Even after run or file deletion and retention processing, bucket usage can lag while background jobs catch up. W\&B doesn't guarantee immediate reclamation of object storage. For an overview of artifacts versus run data, timing expectations, and optional operator actions, see [Manage bucket storage and costs](/platform/hosting/managing-bucket-storage).

<Note>
  If deletions don't appear as expected in the W\&B App when you use the Public API, upgrade the W\&B Python SDK to a current release and retry.
</Note>