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Choosing to “Run in Studio” versus “Run as Job”

Python models can be run on your “local” IDE instance or you can leverage the power of hyper-scaling by running the module as a Job. When running as a job you have access to a number of different machine configurations as follows:

For reference, a typical laptop will be equivalent to either a XS or S machine configuration.

Name CPU RAM Run Rate
Mini 0.5v Core 500MB 0.5
4XS 1v Core 1GB 1
3XS 1v Core 2GB 2
2XS 2v Core 4GB 3
XS 4v Core 8GB 4
S 4v Core 16GB 5
M 6v Core 16GB 6
L 6v Core 32GB 7
XL 8v Core 64GB 8
2XL 8v Core 128GB 9
3XL 10v Core 192GB 10
4XL 10v Core 256GB 11


Complex optimization models may require more CPU cores to solve quickly and large scale simulations may require the use of more RAM due to increase in data required for model fidelity.

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