LocalLLaMA
Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.
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Rules:
Rule 1 - No harassment or personal character attacks of community members. I.E no namecalling, no generalizing entire groups of people that make up our community, no baseless personal insults.
Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.
Rule 3 - No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they're still using the same algorithms since <over 10 years ago>.
Rule 4 - No implying that models are devoid of purpose or potential for enriching peoples lives.
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Are these free to use, or do you have to pay?
free to use if you have the hardware. For this model because of its size, the main problem is the hardware availability/cost. But in general there are 3 ways to run an open weights model:
Is there some sort of calculator to help one determine the best model to run?
Asking chatgpt Claude or any other llm usually is a good starting point
I'm actually curious as to what's the most I can run on an Apple M4 Max system.
How much RAM do you have?
96gb
With Q4 everything below 150B should be fine. You can also run the -Flash variant of this model in Q1, but it is probably not usable.
If I understand the nature of your hardware correctly, you should be able to run the MoE models like Gemma4 26B-A4B or Qwen3.6 35B-A3B at a high quantization fairly performantly.
You could try running some of the dense models (like today's Qwen 3.8 27B) as well, but I expect they'll be pretty slow (judging by my own experience with a unified RAM system that has a Strix Halo APU). Might still be useful for tasks that you can leave running on their own for a long time instead of for interactive chat style interaction though.
You've got enough RAM to load larger models, but there hasn't been much released in between the "it fits on a 24GB or 32GB GPU that a gamer might own" and the "oh god you need HOW MUCH RAM!?" scales lately...