# What's the difference between torch.export / torchserve / executorch / aotinductor?

**URL:** <https://dev-discuss.pytorch.org/t/whats-the-difference-between-torch-export-torchserve-executorch-aotinductor/1642>\
**Category:** deployment\
**Created:** [November 7, 2023, 8:55am UTC](https://dev-discuss.pytorch.org/t/whats-the-difference-between-torch-export-torchserve-executorch-aotinductor/1642 "2023-11-07T08:55:38Z")\
**Posts on this page:** 1\
**Showing post:** 10

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**Author:** ![spiegelball](https://avatars.discourse-cdn.com/v4/letter/s/5f9b8f/32.png) [@spiegelball](https://dev-discuss.pytorch.org/u/spiegelball)\
**Post date:** [February 21, 2024, 11:32pm UTC](https://dev-discuss.pytorch.org/t/whats-the-difference-between-torch-export-torchserve-executorch-aotinductor/1642/10 "2024-02-21T23:32:12Z")

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Thanks for clarification! As I understand now there will be three ways to bring pytorch models to c++:

1. AOTI export .so file and load via runner (the same .so file can be loaded onto different devices like cpu, cuda or mps if I understand your last post right, am I correct)?
2. Load .so file with torchscript (maintainance mode).
3. Capture graph with TorchDynamo and export to torchscript and load torchscript file from c++ as usual (see this comment: [What is the recommend serialization format when considering the upcoming pt2?](https://dev-discuss.pytorch.org/t/what-is-the-recommend-serialization-format-when-considering-the-upcoming-pt2/1088))

Will this work on Windows and on MacOS as well?

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