# Julia vs Numba

**URL:** <https://discourse.julialang.org/t/julia-vs-numba/137116>\
**Category:** Offtopic\
**Tags:** llvm, parallel, jit\
**Created:** [May 14, 2026, 4:03am UTC](https://discourse.julialang.org/t/julia-vs-numba/137116 "2026-05-14T04:03:33Z")\
**Posts on this page:** 1\
**Showing post:** 10

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**Author:** ![stevengj](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/stevengj/32/71_2.png) [@stevengj](https://discourse.julialang.org/u/stevengj)\
**Post date:** [May 14, 2026, 11:42am UTC](https://discourse.julialang.org/t/julia-vs-numba/137116/10 "2026-05-14T11:42:48Z")

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> [@lilachint](#):
>
> And Numba’s compatibility with other tools isn’t that good either,

See also this old post on the (lack of) composability of Numba vs Julia: [Benchmark for latest julia? - #96 by ChrisRackauckas](https://discourse.julialang.org/t/benchmark-for-latest-julia/5991/96)

(@ChrisRackauckas, you might want to update the link in that post, which is broken — the new link is [A "Jupyter" of DiffEq: Introducing Python and R Bindings for DifferentialEquations.jl](https://sciml.ai/news/2018/04/30/Jupyter/))

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