# Julia 1.7 on M1 is Incredible?

**URL:** <https://discourse.julialang.org/t/julia-1-7-on-m1-is-incredible/73498>\
**Category:** Performance\
**Created:** [December 22, 2021, 3:43pm UTC](https://discourse.julialang.org/t/julia-1-7-on-m1-is-incredible/73498 "2021-12-22T15:43:21Z")\
**Posts on this page:** 1\
**Showing post:** 4

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**Author:** ![lawless-m](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lawless-m/32/30869_2.png) [@lawless-m](https://discourse.julialang.org/u/lawless-m)\
**Post date:** [December 23, 2021, 3:50pm UTC](https://discourse.julialang.org/t/julia-1-7-on-m1-is-incredible/73498/4 "2021-12-23T15:50:03Z")

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You are not the first to notice

> [@JuMP.jl and DifferentialEquation.jl benchmarks on M1 Max Julia 1.7.0 x89 vs ARM. (spoiler: ARM is 1.5-2x faster)](https://discourse.julialang.org/t/jump-jl-and-differentialequation-jl-benchmarks-on-m1-max-julia-1-7-0-x89-vs-arm-spoiler-arm-is-1-5-2x-faster/72496):
>
> This is just FYI for fun in case people are interested. I compared JuMP, DiffEq and simple sort() on M1 Max MacBook using official binaries of Julia 1.7.0 with either Native ARM or x86 with Rosetta2. Native ARM version seems to be 1.5-2x faster in JuMP, DiffEq and sort() benchmarks. ARM Julia 1.7 still has a bunch of bugs ([https://github.com/JuliaLang/julia/issues/41440](https://github.com/JuliaLang/julia/issues/41440) and [https://github.com/JuliaLang/julia/issues/41820](https://github.com/JuliaLang/julia/issues/41820)) and even the processor seems to not be recognized correctly ([Feature/CP…](https://github.com/JuliaLang/julia/issues/40876)

It even prompted me to look up the price of a new Macbook. I think I can wait 2x as long for my results 🙂

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