oMLX is so good and efficient ! it’s just like having 500 Nvidia H100’s  !!!
▲ 21 r/oMLX+1 crossposts

oMLX is so good and efficient ! it’s just like having 500 Nvidia H100’s !!!

p.s. this is obviously a joke

u/Clementine-TeX — 11 days ago

M5 Pro, 24 GB UM (17.76 GB VRAM). Help Needed.

I’m on the 14” M5 Pro (15-Core CPU, 16-Core GPU) MacBook Pro with 24 GB unified memory, which according to LM Studio’s System Hardware section gives me 17.76 GB of VRAM.

The models I’m most interested in are (from most to least):

  • Qwen3.5-9B-OptiQ-4bit - For general use (thinking)
  • Gemma-4-12B-it-OptiQ-4bit - For general use (thinking)
  • Qwen3.6-27B-MLX-4bit - For general use (thinking), and some coding (non-thinking)
  • Gemma-4-26B-A4B-it-OptiQ-4bit - For general use (thinking)
  • Qwen3-Coder-30B-A3B-Instruct-MLX-4bit - For coding (non-thinking)

My goal is basically to have a local ChatGPT/Claude “replacement” that’s actually useful day-to-day.

Things I care about:

  • Everything staying local
  • No API costs
  • Vibe Coding help
  • Large LaTeX Manuscript Formatting/Writing
  • Web Re/search
  • As much context as I can realistically get on this hardware

I’ve been tried LM Studio, but noticed that even the 9B models eat up RAM and swap at longer context lengths. Not to mention, they can often get into long loops about nonsense.

As such, I’m considering switching to oMLX, and connecting the models to the internet (to prevent those loops and hallucinations). How shall I go by doing that given my requirements?

I know I shouldn’t expect much, but that’s why I want to maximize what I have, especially since the RAM is a huge bottleneck for me. But I didn’t buy this specifically for Local AI use -- only got interested in it after the fact.

Any advice is appreciated. Thanks.

(P.S. I used AI to revise this post for clarity. English isn’t my first language.)

reddit.com
u/Clementine-TeX — 14 days ago

“You Can’t Game on a Mac”, They Said. (Base M5 Pro)

Minecraft 26.1.2: Fabric & Sodium through Prism, Fabulously Optimized, Complementary Unbound 5.7.1 (High), 32 Chunks for Both Render and Simulation Distance, Sodium Reduce Resolution, Capped at 60 FPS to Limit Jitter, 8 GB of Allocated RAM

u/Clementine-TeX — 2 months ago
▲ 156 r/dbrand+1 crossposts

DBrand 1984

First purchase from DBrand, their Limited Edition 1984 Skin for the 14" M5 Pro. This thing looks great (in my opinion)! Though, t’was a pain in the ass to install.

u/Clementine-TeX — 2 months ago