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Download files

how-to · Reviewed 2026-07-31 · FEAT-0117 GA

The Files tab is the right place to pull data across jobs. To download the output of a single job, work from its Results page instead. See download your results.

From the Files tab​

Select files and use the zipped-download action. Multiple files are compressed first, which can add a few minutes before the transfer starts.

Use the search filters to narrow by date, type, owner, or extension, useful when you want, say, every .out file across a month of jobs.

Single-file and folder limits​

LimitValue
Single download attempt1 GB
View a file in the browserUnder 1 MB
API single-file download5 GB

Above 1 GB, use the Transfer Manager or the CLI. A browser download has no resume. An interruption at 90% means starting over.

Folder downloads flatten the directory structure

Downloading a folder gives you a flat list of files, not the tree.

This matters for multi-run jobs, where several runs can produce files with the same name. They will collide. Download runs individually, or use the Transfer Manager, which preserves structure.

From a job that's still running​

You don't have to wait for a job to finish.

  • Snapshot captures every file in a run at a point in time, from the Active Runs table. See live tailing and snapshots.

  • scp copies files off the cluster directly, if you've configured SSH access. Job files live in ~/work/:

    scp -i ~/.ssh/<private-key> <cluster-id>:~/work/process_output.log ~/local/path/

    Reverse the arguments to push a file to the cluster. Wildcards work: velocity-contour-*.

    On Windows, WinSCP does the same over SFTP, set the protocol to SFTP, the host to the cluster IP, and the username to the job ID.

Bulk and scripted downloads​

You wantUse
Everything from one job, fastTransfer Manager
Specific files matched by patternTransfer Manager filters
Many jobs, scriptedRescale CLI, looping over job IDs
Output as soon as jobs finishTransfer Manager automatic downloads

Consider not downloading at all​

If you're going to post-process the data anyway, attach the job to a workstation and work with the files in place. No transfer, and you get visualization hardware. For a large result set this is usually faster.

Troubleshooting​