# Performance: Julia/JuMP vs. Python/Pyomo

**URL:** <https://discourse.julialang.org/t/performance-julia-jump-vs-python-pyomo/92044>\
**Category:** Optimization (Mathematical)\
**Created:** [December 23, 2022, 10:44am UTC](https://discourse.julialang.org/t/performance-julia-jump-vs-python-pyomo/92044 "2022-12-23T10:44:58Z")\
**Posts on this page:** 1\
**Showing post:** 21

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**Author:** ![miles.lubin](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/miles.lubin/32/279_2.png) [@miles.lubin](https://discourse.julialang.org/u/miles.lubin)\
**Post date:** [July 9, 2023, 9:26pm UTC](https://discourse.julialang.org/t/performance-julia-jump-vs-python-pyomo/92044/21 "2023-07-09T21:26:06Z")

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EDIT: This thread is cited from a blog post by GAMS: [Performance in Optimization Models: A Comparative Analysis of GAMS, Pyomo, GurobiPy, and JuMP](https://www.gams.com/blog/2023/07/performance-in-optimization-models-a-comparative-analysis-of-gams-pyomo-gurobipy-and-jump/). It was originally cited in a way that suggested that JuMP developers collaborated on the blog post. The blog post has since been corrected. I’ve locked the thread to preserve the discussion in its original context.

The JuMP developers’ response: [JuMP, GAMS, and the IJKLM model | JuMP](https://jump.dev/2023/07/20/gams-blog/).

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