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I have a flow with 4 models (xgboost) configured from the visual ML interface. If I run them there each training takes less than a minute to compute.

However when I start the job training in the flow of the 4 models it takes up to 60 min and more ... I did not have the nerve and aborted them early.
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Have you checked that the sampling settings on the Train recipe in the flow are the same that your analysis?
Hi, Did you find the source of the discrepancy?
No . I did not. My dataset is well below the standard setting of first 10.000 rows.

It is extremely annoying ! Instead of 20 secs it is now again calculating for 20 min as soon as I start 2-3 training jobs in parallel.
Could you please attach a diagnostic of the affected job ? From the job page, click on Actions > Download job diagnosis.
If the resulting file is too large for mail (> 15 MB), you can use a file transfer service like WeTransfer to get it to us

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