# Julia 1.9 (not yet downloadable) and 1.8

**URL:** <https://discourse.julialang.org/t/julia-1-9-not-yet-downloadable-and-1-8/76708>\
**Category:** General Usage\
**Created:** [February 18, 2022, 4:30pm UTC](https://discourse.julialang.org/t/julia-1-9-not-yet-downloadable-and-1-8/76708 "2022-02-18T16:30:27Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Palli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/palli/32/3380_2.png) [@Palli](https://discourse.julialang.org/u/Palli)\
**Post date:** [February 18, 2022, 4:30pm UTC](https://discourse.julialang.org/t/julia-1-9-not-yet-downloadable-and-1-8/76708/1 "2022-02-18T16:30:27Z")

</div>

I just downloaded the Julia nightly to get Julia 1.9-DEV that is now on master. 1.8-beta1 seems close.

I actually get:

```julia
  | | |_| | | | (_| | | Version 1.8.0-DEV.1505 (2022-02-12)
 _/ |\ __'_|_|_|\__'_| | Commit e422590151 (5 days old master)

```

so it’s not actually a “nightly”… I’m not rushing people, just letting know.

I was meaning to test out a rather recent (2-day old) PR:

[https://github.com/JuliaLang/julia/pull/43800](https://github.com/JuliaLang/julia/pull/43800)

and benchmark, see if LLVM 13 makes a difference. I’ll wait.

EDIT:  
Anyway, I get 1.16 sec (22%) faster (51% fewer allocations and 42% less in MB) on unloaded or lightly loaded machine (load average had gone down to about 0.5) on startup:

```julia
julia> @time using PythonCall
  4.225816 seconds (2.42 M allocations: 170.252 MiB, 1.07% gc time, 85.06% compilation time)

vs.
julia> @time using PythonCall
  5.386591 seconds (4.98 M allocations: 296.372 MiB, 1.52% gc time, 89.29% compilation time)

```

startup of julia process (while loaded) was slightly slower by 30 ms.

Below same test while machine loaded, before I did: `kill -SIGSTOP <firefox-process-main-PID>` (and later corresponding kill -SIGCONT to unfreeze).

I seem to be be getting ca. 1+ sec. (20%) faster on startup:

```julia
julia> @time using PythonCall
  4.919860 seconds (2.42 M allocations: 170.254 MiB, 1.03% gc time, 85.55% compilation time)

vs. in 1.7

julia> @time using PythonCall
  6.114529 seconds (4.98 M allocations: 296.368 MiB, 1.60% gc time, 89.13% compilation time)

```

What do others get? My (loaded) machine has some noise, I try several times to get minimum time (`@btime` doesn’t work for this). I know the author gets 2.5 sec… maybe his machine is super-fast or mine just too loaded.