this post was submitted on 17 Jun 2026
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[–] NotMyOldRedditName@lemmy.world 2 points 15 hours ago* (last edited 14 hours ago) (1 children)

Also developers often want more ram, and if youre on the mac side, the M series ram works as video ram for loading and running models, so there's a good chance you can already run something better than is typical of others, and apple is focusing on this by adding more NPUs and increasing memory bandwidth. They arent good at training, but can do inference.

[–] partofthevoice@lemmy.zip 1 points 12 hours ago (2 children)

I’m on a MacBook with M2, 32GB ram. Literally just tried:

  • gemma4:12b - very slow, unworkable
  • qwen3:8b - very slow, unworkable
  • qwen2.5-coder:7b - slow but workable. Doesn’t use tools properly in OpenCode.

Well, I guess I’ll try again next year.

For context: my home pc is running gemma4:31b just fine. It’s also a beefy ass desktop, though.

[–] fluxx@mander.xyz 1 points 38 minutes ago

Are you running an mlx model? If not, try that. My m4 macbook runs qwen3.6-35b-a3b lightning fast. Has its issues, but fast nonetheless.

[–] NotMyOldRedditName@lemmy.world 2 points 12 hours ago* (last edited 12 hours ago)

You might be doing something wrong, models that size shouldn't be that slow if properly configured on a 32gb m2

You need a metal optimized client and model, not the same models you'd run on your desktop machine.