CPUbenchmark.net is the best way to compare 2 CPUs.

Directly comparing cores and speed is only useful across the same architecture, comparing brands and different generations should only be done via benchmarks.

I can’t provide any feedback about if those CPUs are enough for immich as I do not use it.

The move from php to go and the slowness of NC is what attracted me to the project. But I’m going to wait a bit longer until we’re flush with 3rd party setup guides cause I simply do not have the time to wade through their docs.

I had very similar experiences with OCIS. Got it all set up following the quick start guide, found extremely odd and unacceptable behaviour with storage space ballooning, start troubleshooting and find “oh you had to do this, this and this manually, it’s in the docs” It is in the docs, but never referenced by any other part of the docs. Because why would you mention the thing that the admin must manually set up in 100% of installs in your setup guide?

Anyway I’ve become that guy ranting on the internet that I don’t want to be. So just so you don’t suffer as much as I did; you have to create scheduled tasks via cron or your preference of scheduler to clean your uploads folder and data blobs. This also did not fix my specific issue and I ended up giving up on OCIS and sticking to Nextcloud.

I struggled to get it set up last night, eventually I stumbled across issue 796 on the github which had the solution. https://github.com/neonbjb/tortoise-tts/issues/796#issuecomment-2204846504

Seems there’s an issue with the dependencies currently and all versions of installing tortoise-tts from the existing instructions is doomed to failure without manual intervention.

As mikejgrecojr commented in the linked github issue, the fix for running via docker is:

Try updating your Dockerfile by adding in scipy to the conda install and specifying version 1.13.1 on line 31 like below. That worked for me:

&& conda install pytorch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 pytorch-cuda=12.1 scipy=1.13.1 -c pytorch -c