Is it a good time to buy an Arm macbook to learn and play Julia?

Hi, I’m a grad student who is very interested in Julia. Since my laptop is almost 6-year old and slow, I’m considering and looking forward to buying an apple-silicon MacBook as my major work device. However, aware of this issue being open, I’m not sure when it is a good time to move to arm mac? I just experienced the benefits of Julia like the BigFloat for high-precision, Pluto for tutorials… I don’t want to give up them :smile: Also, I want to keep learning Julia.

So could anyone please help me with the following? Thanks.

  • The topic question.
  • If it is not a good time, then when will it be?
  • Any other suggestions will be appreciated.
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I have no experience with ARM MacBooks, but do have experience with development on ARM. It is fine if you’re using only the packages that work for ARM, but you will probably keep bumping into issues where some dependency or tool is not built for ARM.

My knowledge isn’t very up-to-date though. Maybe @giordano can tell a bit more about this?

Multiple users have reported good experiences with running Julia on Rosetta, so even without native M1 support, you should still be able to run everything. At some point in the not-very-far future there will be a native release, which should allow you to really get the most out of your hardware.


I don’t think I’m the best person who can comment on this, but here we go :grinning_face_with_smiling_eyes: While Julia can be built natively for the new platform, using the development version, do note that vast majority of third-party packages which rely down their stack on binary libraries won’t work just yet. It’ll take time (look for months) for the ecosystem to catch up. For the time being you can consider using Julia with Rosetta 2.

In general, if you don’t want to use Julia via Rosetta 2 I’d recommend buying this machine if you want to be an early adopter, eager to report any bugs you may find (not already reported and tracked somewhere, like the general unavailability of binary dependencies) and be able to deal with some issues on your own.


Thanks! It is nice to know that Julia on Rosetta works pretty well.

Thanks you and @rikh. Really appreciate the detailed explanation. I will consider giving it a try via Rosetta and report the issues I might come across.

Regardless of what you buy, now seems like the right time to buy since you say your current offering is 6 years old. You are a grad student – that machine is your livelihood! Invest in a new one.


( not tested )
IMHO: the other alternative is the Docker Desktop for Apple silicon | Docker Documentation
and using “linux/arm64/v8” images → arm64v8/julia ,

I just ordered a new M1 macbook and expect to be using Rosetta for a while. Nothing I’ve heard about this is bad and I’m expecting a serious performance boost once Julia and the packages I use run in native mode.

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Thanks for the suggestion. I am not familiar with Docker(and will check it later). Will it affect the performance or something?

yeah~ that’s right :+1:

Having a computer may be indispensable, but a particular machine is just a tool, mostly interchangeable (data should be backed up). I would go for something less expensive, probably an x86 for programming, and maybe replace more often than every 6 years. YMMV


If you are on a student budget but want to use ARM, another option is PINEBOOK Pro | PINE64
It comes installed with Manjaro Linux (just a customised version of Arch Linux).
Definitely slower than an M1 but a lot cheaper. Plus more customisable since its not OSX. The aarch64 binaries downloadable from Download Julia and the nightly builds always work for me. I don’t use that many packages so don’t know about any binary issues.